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Conversational Commerce Strategy
Conversational Commerce Strategy

AI in CX Webinar Recap: Building a Conversational Commerce Strategy that Converts

0 min read . By Gabrielle Policella

TL;DR:

  • Implement quickly and optimize continuously. Cornbread's rollout was three phases: audit knowledge base, launch, then refine. Stacy conducts biweekly audits and provides daily AI feedback to ensure responses are accurate and on-brand.
  • Simplify your knowledge base language. Before BFCM, Stacy rephrased all guidance documentation to be concise and straightforward so Shopping Assistant could deliver information quickly without confusion.
  • Use proactive suggested questions. Most of Cornbread's Shopping Assistant engagement comes from Suggested Product Questions that anticipate customer needs before they even ask.
  • Treat AI as another team member. Make sure the tone and language AI uses match what human agents would say to maintain consistent customer relationships.
  • Free up agents for high-value work. With AI handling straightforward inquiries, Cornbread's CX team expanded into social media support, launched a retail pop-up shop, and has more time for relationship-building phone calls.

Customer education has become a critical factor in converting browsers into buyers. For wellness brands like Cornbread Hemp, where customers need to understand ingredients, dosages, and benefits before making a purchase, education has a direct impact on sales. The challenge is scaling personalized education when support teams are stretched thin, especially during peak sales periods.

Katherine Goodman, Senior Director of Customer Experience, and Stacy Williams, Senior Customer Experience Manager, explain how implementing Gorgias's AI Shopping Assistant transformed their customer education strategy into a conversion powerhouse. 

In our second AI in CX episode, we dive into how Cornbread achieved a 30% conversion rate during BFCM, saving their CX team over four days of manual work.

Top learnings from Cornbread's conversational commerce strategy

1. Customer education drives conversions in wellness

Before diving into tactics, understanding why education matters in the wellness space helps contextualize this approach.

Katherine, Senior Director of Customer Experience at Cornbread Hemp, explains:

"Wellness is a very saturated market right now. Getting to the nitty-gritty and getting to the bottom of what our product actually does for people, making sure they're educated on the differences between products to feel comfortable with what they're putting in their body."

The most common pre-purchase questions Cornbread receives center around three areas: ingredients, dosages, and specific benefits. Customers want to know which product will help with their particular symptoms. They need reassurance that they're making the right choice.

What makes this challenging: These questions require nuanced, personalized responses that consider the customer's specific needs and concerns. Traditionally, this meant every customer had to speak with a human agent, creating a bottleneck that slowed conversions and overwhelmed support teams during peak periods.

2. Shopping Assistant provides education that never sleeps

Stacy, Senior Customer Experience Manager at Cornbread, identified the game-changing impact of Shopping Assistant:

"It's had a major impact, especially during non-operating hours. Shopping Assistant is able to answer questions when our CX agents aren't available, so it continues the customer order process."

A customer lands on your site at 11 PM, has questions about dosage or ingredients, and instead of abandoning their cart or waiting until morning for a response, they get immediate, accurate answers that move them toward purchase.

The real impact happens in how the tool anticipates customer needs. Cornbread uses suggested product questions that pop up as customers browse product pages. Stacy notes:

"Most of our Shopping Assistant engagement comes from those suggested product features. It almost anticipates what the customer is asking or needing to know."

Actionable takeaway: Don't wait for customers to ask questions. Surface the most common concerns proactively. When you anticipate hesitation and address it immediately, you remove friction from the buying journey.

3. Implementation follows a clear three-phase approach

One of the biggest myths about AI is that implementation is complicated. Stacy explains how Cornbread’s rollout was a straightforward three-step process: audit your knowledge base, flip the switch, then optimize.

"It was literally the flip of a switch and just making sure that our data and information in Gorgias was up to date and accurate." 

Here's Cornbread’s three-phase approach:

  1. Preparation. Before launching, Cornbread conducted a comprehensive audit of their knowledge base to ensure accuracy and completeness. This groundwork is critical because your AI is only as good as the information it has access to.
  2. Launch and training. After going live, the team met weekly with their Gorgias representative for three to four weeks. They analyzed engagements, reviewed tickets, and provided extensive AI feedback to teach Shopping Assistant which responses were appropriate and how to pull from the knowledge base effectively.
  3. Ongoing optimization. Now, Stacy conducts audits biweekly and continuously updates the knowledge base with new products, promotions, and internal changes. She also provides daily AI feedback, ensuring responses stay accurate and on-brand.

Actionable takeaway: Block out time for that initial knowledge base audit. Then commit to regular check-ins because your business evolves, and your AI should evolve with it.

Read more: AI in CX Webinar Recap: Turning AI Implementation into Team Alignment

4. Simple, concise language converts better

Here's something most brands miss: the way you write your knowledge base articles directly impacts conversion rates.

Before BFCM, Stacy reviewed all of Cornbread's Guidance and rephrased the language to make it easier for AI Agent to understand. 

"The language in the Guidance had to be simple, concise, very straightforward so that Shopping Assistant could deliver that information without being confused or getting too complicated," Stacy explains. When your AI can quickly parse and deliver information, customers get faster, more accurate answers. And faster answers mean more conversions.

Katherine adds another crucial element: tone consistency.

"We treat AI as another team member. Making sure that the tone and the language that AI used were very similar to the tone and the language that our human agents use was crucial in creating and maintaining a customer relationship."

As a result, customers often don't realize they're talking to AI. Some even leave reviews saying they loved chatting with "Ally" (Cornbread's AI agent name), not realizing Ally isn't human.

Actionable takeaway: Review your knowledge base with fresh eyes. Can you simplify without losing meaning? Does it sound like your brand? Would a customer be satisfied with this interaction? If not, time for a rewrite.

Read more: How to Write Guidance with the “When, If, Then” Framework

5. Black Friday results proved the strategy works under pressure

The real test of any CX strategy is how it performs under pressure. For Cornbread, Black Friday Cyber Monday 2025 proved that their conversational commerce strategy wasn't just working, it was thriving.

Over the peak season, Cornbread saw: 

  • Shopping Assistant conversion rate jumped from a 20% baseline to 30% during BFCM
  • First response time dropped from over two minutes in 2024 to just 21 seconds in 2025
  • Attributed revenue grew by 75%
  • Tickets doubled, but AI handled 400% more tickets compared to the previous year
  • CSAT scores stayed exactly in line with the previous year, despite the massive volume increase

Katherine breaks down what made the difference:

"Shopping Assistant popping up, answering those questions with the correct promo information helps customers get from point A to point B before the deal ends."

During high-stakes sales events, customers are in a hurry. They're comparing options, checking out competitors, and making quick decisions. If you can't answer their questions immediately, they're gone. Shopping Assistant kept customers engaged and moving toward purchase, even when human agents were swamped.

Actionable takeaway: Peak periods require a fail-safe CX strategy. The brands that win are the ones that prepare their AI tools in advance.

6. Strategic work replaces reactive tasks

One of the most transformative impacts of conversational commerce goes beyond conversion rates. What your team can do with their newfound bandwidth matters just as much.

With AI handling straightforward inquiries, Cornbread's CX team has evolved into a strategic problem-solving team. They've expanded into social media support, provided real-time service during a retail pop-up, and have time for the high-value interactions that actually build customer relationships.

Katherine describes phone calls as their highest value touchpoint, where agents can build genuine relationships with customers. “We have an older demographic, especially with CBD. We received a lot of customer calls requesting orders and asking questions. And sometimes we end up just yapping,” Katherine shares. “I was yapping with a customer last week, and we'd been on the call for about 15 minutes. This really helps build those long-term relationships that keep customers coming back."

That's the kind of experience that builds loyalty, and becomes possible only when your team isn't stuck answering repetitive tickets.

Stacy adds that agents now focus on "higher-level tickets or customer issues that they need to resolve. AI handles straightforward things, and our agents now really are more engaged in more complicated, higher-level resolutions."

Actionable takeaway: Stop thinking about AI only as a cost-cutting tool and start seeing it as an impact multiplier. The goal is to free your team to work on conversations that actually move the needle on customer lifetime value.

7. Continuous optimization for January and beyond

Cornbread isn't resting on their BFCM success. They're already optimizing for January, traditionally the biggest month for wellness brands as customers commit to New Year's resolutions.

Their focus areas include optimizing their product quiz to provide better data to both AI and human agents, educating customers on realistic expectations with CBD use, and using Shopping Assistant to spotlight new products launching in Q1.

Build your conversational commerce strategy now

The brands winning at conversational commerce aren't the ones with the biggest budgets or the largest teams. They're the ones who understand that customer education drives conversions, and they've built systems to deliver that education at scale.

Cornbread Hemp's success comes down to three core principles: investing time upfront to train AI properly, maintaining consistent optimization, and treating AI as a team member that deserves the same attention to tone and quality as human agents.

As Katherine puts it:

"The more time that you put into training and optimizing AI, the less time you're going to have to babysit it later. Then, it's actually going to give your customers that really amazing experience."

Watch the replay of the whole conversation with Katherine and Stacy to learn how Gorgias’s Shopping Assistant helps them turn browsers into buyers. 

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By Gabrielle Policella

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Featured articles

Conversational Commerce Metrics

Your Support Team Drives More Revenue Than You Think: Conversational Commerce Metrics

Your chat might be closing more sales than your checkout page. Here’s how to measure it.
By Tina Donati
0 min read . By Tina Donati

TL;DR:

  • Support chats can now be directly tied to revenue. Brands are measuring conversations by conversion rate, average order value (AOV), and GMV influenced.
  • AI resolution rate is only valuable if the answers are accurate and helpful. A high resolution rate doesn’t matter if it leads to poor recommendations — the best AI both deflects volume and drives confident purchases.
  • Chat conversion rates often outperform traditional channels. Brands like Arc’teryx saw a 75% lift in conversions (from 4% to 7%) when AI handled high-intent product questions.
  • Shoppers who chat often spend more. Conversations lead to higher AOVs by helping customers understand products, explore upgrades, and discover add-ons — not just through upselling, but smarter guidance.

Conversational commerce finally has a scoreboard.

For years, CX leaders knew support conversations mattered, they just couldn’t prove how much. Conversations lived in that gray area of ecommerce where shoppers got answers, agents did their best, and everyone agreed the channel was “important”… 

But tying those interactions back to actual revenue? Nearly impossible.

Fast forward to today, and everything has changed.

Real-time conversations — whether handled by a human agent or powered by AI — now leave a measurable footprint across the entire customer journey. You can see how many conversations directly influenced a purchase. 

In other words, conversational commerce is finally something CX teams can measure, optimize, and scale with confidence.

Why measuring conversational commerce matters now

If you want to prove the value of your CX strategy to your CFO, your marketing team, or your CEO, you need data, not anecdotes.

Leadership isn’t swayed by “We think conversations help shoppers.” They want to see the receipts. They want to know exactly how interactions influence revenue, which conversations drive conversion, and where AI meaningfully reduces workload without sacrificing quality.

That’s why conversational commerce metrics matter now more than ever. This gives CX leaders a way to:

  • Quantify the revenue influence of conversations
  • Understand where AI improves efficiency — and where humans add the most value
  • Make informed decisions on staffing, automation, and channel investment
  • Turn CX into a profit center instead of a cost center

These metrics let you track impact with clarity and confidence.

And once you can measure it, you can build a stronger case for deeper investment in conversational tools and strategy.

The 4 metric categories that define conversational commerce success

So, what exactly should CX teams be measuring?

While conversational commerce touches every part of the customer journey, the most meaningful insights fall into four core categories: 

  1. Automation performance
  2. Conversion & revenue impact
  3. Engagement quality
  4. Discounting behavior

Let’s dive into each.

Automation performance metrics

If you want to understand how well your conversational commerce strategy is working, automation performance is the first place to look. These metrics reveal how effectively AI is resolving shopper needs, reducing ticket volume, and stepping into revenue-driving conversations at scale.

The two most foundational metrics?

1. Resolution rate: Are AI-led conversations actually helpful?

Resolution rate measures how many conversations your AI handles from start to finish without needing a human to take over. On paper, high resolution rates sound like a guaranteed win. It suggests your AI is handling product questions, sizing concerns, shade matching, order guidance, and more — all without adding to your team’s workload.

But a high resolution rate doesn’t automatically mean your AI is performing well.

Yes, the ticket was “resolved,” but was the customer actually helped? Was the answer accurate? Did the shopper leave satisfied or frustrated?

This is where quality assurance becomes essential. Your AI should be resolving tickets accurately and helpfully, not simply checking boxes.

At its best, a strong resolution rate signals that your AI is:

  • Confidently answering product questions
  • Guiding shoppers to the right SKU, variant, shade, size, or style
  • Reducing cart abandonment caused by confusion
  • Helping pre-sale shoppers convert faster

When resolution rate quality goes up, so does revenue influence.

You can see this clearly with beauty brands, where accuracy matters enormously. bareMinerals, for example, used to receive a flood of shade-matching questions. Everything from “Which concealer matches my undertone?” to “This foundation shade was discontinued; what’s the closest match?” 

Before AI, these questions required well-trained agents and often created inconsistencies depending on who answered.

Once they introduced Shopping Assistant, resolution rate suddenly became more meaningful. AI wasn’t just closing tickets; it was giving smarter, more confident recommendations than many agents could deliver at scale, especially after hours. 

BareMinerals' AI Agent recommends a customer a foundation that matches their skin tone

That accuracy paid off. 

AI-influenced purchases at bareMinerals had zero returns in the first 30 days because customers were finally getting the right shade the first time.

That’s the difference between “resolved” and resolved well.

2. Zero-touch tickets: How many tickets never reach a human?

The zero-touch ticket rate measures something slightly different: the percentage of conversations AI manages entirely on its own, without ever being escalated to an agent.

This metric is a direct lens into:

  • Workload reduction
  • Team efficiency
  • Cost savings
  • AI’s ability to own high-volume question types

More importantly, deflection widens the funnel for more revenue-driven conversations.

When AI deflects more inbound questions, your support team can focus on conversations that truly require human expertise, including returns exceptions, escalations, VIP shoppers, and emotionally sensitive interactions.

Brands with strong deflection rates typically see:

  • Shorter wait times
  • Higher CSAT
  • Lower support costs
  • More AI-influenced revenue

Conversion and revenue impact metrics

If automation metrics tell you how well your AI is working, conversion and revenue metrics tell you how well it’s selling.

This category is where conversational commerce really proves its value because it shows the direct financial impact of every human- or AI-led interaction.

1. Chat Conversion Rate (CVR): How often do conversations turn into purchases?

Chat conversion rate measures the percentage of conversations that end in a purchase, and it’s one of the clearest indicators of whether your conversational strategy is influencing shopper decisions.

A strong CVR tells you that conversations are:

  • Building confidence
  • Removing hesitation
  • Guiding shoppers toward the right product

You see this clearly with brands selling technical or performance-driven products. 

Outdoor apparel shoppers, for example, don’t just need “a jacket” — they need to know which jacket will hold up in specific temperatures, conditions, or terrains. A well-trained AI can step into that moment and convert uncertainty into action.

Arc’teryx saw this firsthand. 

Arc'teryx uses Shopping Assistant to enable purchases directly from chat

Once Shopping Assistant started handling their high-intent pre-purchase questions, their chat conversion rate jumped dramatically — from 4% to 7%. A 75% lift. 

That’s what happens when shoppers finally get the expert guidance they’ve been searching for.

2. GMV influenced: The revenue ripple effect of conversations

Not every shopper buys the moment they finish a chat. Some take a few hours. Some need a day or two. Some want to compare specs or read reviews before committing.

GMV influenced captures this “tail effect” by tracking revenue within 1–3 days of a conversation.

It’s especially powerful for:

  • High-consideration purchases (like outdoor gear, home furniture, equipment)
  • Products with many options, specs, or configurations
  • Shoppers who need reassurance before buying

In Arc’teryx’s case, shoppers often take time to confirm they’re choosing the right technical gear.

Yet even with that natural pause in behavior, Shopping Assistant still influenced 3.7% of all revenue, not by forcing instant decisions, but by providing the clarity people needed to make the right one.

3. AOV from conversational commerce: Do conversations lead to bigger carts?

This metric looks at the average order value of shoppers who engage in a conversation versus those who don’t. 

If the conversational AOV is higher, it means your AI or agents are educating customers in ways that naturally expand the cart.

Examples of AOV-lifting conversations include:

  • Recommending complementary gear, tools, or accessories
  • Suggesting upgraded options based on needs
  • Helping shoppers understand the difference between product tiers
  • Explaining why a specific product is worth the investment

When conversations are done well, AOV increases not because shoppers are being upsold, but because they’re being guided. 

4. ROI of AI-powered conversations: The metric your leadership cares most about

ROI compares the revenue generated by conversational AI to the cost of the tool itself — in short, this is the number that turns heads in boardrooms.

Strong ROI shows that your AI:

  • Does the work of multiple agents
  • Drives new revenue, not just ticket deflection
  • Provides accurate answers consistently, at any time
  • Delivers a high-quality experience without expanding headcount

When ROI looks like that, AI stops being a “tool” and starts being an undeniable growth lever.

Related: The hidden power and ROI of automated customer support

Engagement metrics that indicate purchase intent

Not every metric in conversational commerce is a final outcome. Some are early signals that show whether shoppers are interested, paying attention, and moving closer to a purchase.

These engagement metrics are especially valuable because they reveal why conversations convert, not just whether they do. When engagement goes up, conversion usually follows.

1. Click-Through Rate (CTR): Are shoppers acting on the products your AI recommends?

CTR measures the percentage of shoppers who click the product links shared during a conversation. It’s one of the cleanest leading indicators of buyer intent because it reflects a moment where curiosity turns into action.

If CTR is high, it’s a sign that:

  • Your recommendations are relevant
  • The conversation is persuasive
  • The shopper trusts the guidance they’re getting
  • The AI is surfacing the right product at the right time

In other words, CTR tells you which conversations are influencing shopping behavior.

And the connection between CTR and revenue is often tighter than teams expect.

Just look at what happened with Caitlyn Minimalist. When they began comparing the results of human-led conversations versus AI-assisted ones over a 90-day period, CTR became one of the clearest predictors of success. Their Shopping Assistant consistently drove meaningful engagement with its recommendations — an 18% click-through rate on the products it suggested.

That level of engagement translated directly into better outcomes:

  • AI-driven conversations converted at 20%, compared to just 8% for human agents
  • Many of those clicks led to multi-item purchases
  • Overall, the brand experienced a 50% lift in sales from AI-assisted chats compared to human-only ones

When shoppers click, they’re moving deeper into the buying cycle. Strong CTR makes it easier to forecast conversion and understand how well your conversational flows are guiding shoppers toward the right products.

AI Agent recommends a customer with jewelry safe for sensitive skin

Discounting behavior metrics

Discounting can be one of the fastest ways to nudge a shopper toward checkout, but it’s also one of the fastest ways to erode margins. 

That’s why discount-related metrics matter so much in conversational commerce. 

They show not just whether AI is using discounts, but how effectively those discounts are driving conversions.

1. Discounts offered: Are incentives being used strategically or too often?

This metric tracks how many discount codes or promotional offers your AI is sharing during conversations. 

Ideally, discounts should be purposeful — timed to moments when a shopper hesitates or needs an extra nudge — not rolled out as a one-size-fits-all script. When you monitor “discounts offered,” you can ensure that incentives are being used as conversion tools, not crutches.

This visibility becomes particularly important at high-intent touchpoints, such as exit intent or cart recovery interactions, where a small incentive can meaningfully increase conversion if used correctly.

2. Discounts applied: Are those discounts actually influencing the purchase?

Offering a discount is one thing. Seeing whether customers use it is another.

A high “discounts applied” rate suggests:

  • The offer was compelling
  • The timing was right
  • The shopper truly needed that incentive to convert

A low usage rate tells a different story: Your team (or your AI) is discounting unnecessarily.

This metric alone often surprises brands. More often than not, CX teams discover they can discount less without hurting conversion, or that a non-discount incentive (like a relevant product recommendation) performs just as well.

Understanding this relationship helps teams tighten their promotional strategy, protect margins, and use discounts only where they actually drive incremental revenue.

How CX teams use these metrics to make better decisions

Once you know which metrics matter, the next step is building a system that brings them together in one place.

Think of your conversational commerce scorecard as a decision-making engine — something that helps you understand performance at a glance, spot bottlenecks, optimize AI, and guide shoppers more effectively.

In Gorgias, you can customize your analytics dashboard to watch the metrics that matter most to your brand. This becomes the single source of truth for understanding how conversations influence revenue.

Here’s what a powerful dashboard unlocks:

1. You learn where AI performs best (and where humans outperform)

Some parts of the customer journey are perfect for AI: repetitive questions, product education, sizing guidance, shade matching, order status checks. 

Others still benefit from human support, like emotional conversations, complex troubleshooting, multi-item styling, or high-value VIP concerns.

Metrics like resolution rate, zero-touch ticket rate, and chat conversion rate show you exactly which is which.

When you track these consistently, you can:

  • Identify conversation types AI should fully own
  • Spot where AI needs more training
  • Allocate human agents to higher-value conversations
  • Decide when humans should step in to drive stronger outcomes

For example, if AI handles 80% of sizing questions successfully but struggles with multi-item styling advice, that tells you where to invest in improving AI, and where human expertise should remain the default.

2. You uncover what shoppers actually need to convert

Metrics like CTR, CVR, and conversational AOV reveal the inner workings of shopper decision-making. They show which recommendations resonate, which don’t, and which messaging actually moves someone to purchase.

With these insights, CX teams can:

  • Refine product recommendations
  • Improve conversation flows that stall out
  • Adjust the tone or structure of AI messaging
  • Draft stronger scripts for human agents
  • Identify recurring questions that indicate missing PDP information

For instance, if shoppers repeatedly ask clarifying questions about a product’s material or fit, that’s a signal for merchandising or product teams. 

If recommendations with social proof get high engagement, marketing can integrate that insight into on-site messaging. 

Conversations reveal what customers really care about — often before analytics do.

3. You prove that conversations directly drive revenue

This is the moment when the scorecard stops being a CX tool and becomes a business tool.

A clear set of metrics shows how conversations tie to:

  • GMV influenced
  • AOV lift
  • Revenue generated by AI
  • ROI of conversational commerce tools

When a CX leader walks into a meeting and says, “Our AI Assistant influenced 5% of last month’s revenue” or “Conversational shoppers have a 20% higher AOV,” the perception of CX changes instantly.

You’re no longer a support cost. You’re a revenue channel.

And once you have numbers like ROI or revenue influence in hand, it becomes nearly impossible for anyone to argue against further investment in CX automation.

4. You identify where shoppers are dropping off or hesitating

A scorecard doesn’t just show what’s working, it surfaces what’s not.

Metrics make friction obvious:

Metric Signal

What It Means

Low CTR

Recommendations may be irrelevant or poorly timed.

Low CVR

Conversations aren’t persuasive enough to drive a purchase.

High deflection but low revenue

AI is resolving tickets, but not effectively selling.

High discount usage

Shoppers rely on incentives to convert.

Low discount usage

You may be offering discounts unnecessarily and losing margin.

Once you identify these patterns, you can run targeted experiments:

  • Test new scripts or flows
  • Adjust product recommendations
  • Add social proof or benefit framing
  • Reassess discounting strategies
  • Rework messaging on key PDPs

Compounded over time, these moments create major lifts in conversion and revenue.

5. You create a feedback loop across marketing, merchandising, and product

One of the biggest hidden values of conversational data is how it strengthens cross-functional decision-making.

A clear analytics dashboard gives teams visibility into:

  • Unclear or missing product information (from repeated questions)
  • Merchandising opportunities (from your most popular products)
  • Landing page or PDP improvements (from drop-off points)
  • Messaging that resonates with real customers (from AI messages)

Suddenly, CX isn’t just answering questions — it’s informing strategy across the business.

CX drives revenue when you measure what matters

With the right metrics in place, CX leaders can finally quantify the impact of every interaction, and use that data to shape smarter, more profitable customer journeys.

If you're ready to measure — and scale — the impact of your conversations, tools like Gorgias AI Agent and Shopping Assistant give CX teams the visibility, accuracy, and performance needed to turn every interaction into revenue.

Want to see it in action? Book a demo and discover what conversational commerce can do for your bottom line.

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min read.
AI Alignment

AI in CX Webinar Recap: Turning AI Implementation into Team Alignment

By Gabrielle Policella
0 min read . By Gabrielle Policella

TL;DR:

  • Implement quickly and iterate. Rhoback’s initial rollout process took two weeks, right before BFCM. Samantha moved quickly, starting with basic FAQs and then continuously optimizing.  
  • Train AI like a three-year-old. Although it is empathetic, an AI Agent does not inherently know what is right or wrong. Invest in writing clear Guidance, testing responses, and ensuring document accuracy. 
  • Approach your AI’s tone of voice like a character study. Your AI Agent is an extension of your brand, and its personality should reflect that. Rhoback conducted a complete analysis of its agent’s tone, age, energy, and vocabulary. 
  • Embrace AI as a tool to reveal inconsistencies. If your AI Agent is giving inaccurate information, it’s exposing gaps in your knowledge sources. Uses these early test responses to audit product pages, help center content, Guidance, and policies.
  • Check in regularly and keep humans in control. Introduce weekly reviews or QA rituals to refine AI’s accuracy, tone, and efficiency. Communicate AI insights cross-functionally to build trust and work towards shared goals.

When Rhoback introduced an AI Agent to its customer experience team, it did more than automate routine tickets. Implementation revealed an opportunity to improve documentation, collaborate cross-functionally, and establish a clear brand tone of voice. 

Samantha Gagliardi, Associate Director of Customer Experience at Rhoback, explains the entire process in the first episode of our AI in CX webinar series.

Top learnings from Rhoback’s AI rollout  

1. You can start before you “feel ready”

With any new tool, the pre-implementation phase can take some time. Creating proper documentation, training internal teams, and integrating with your tech stack are all important steps that happen before you go live. 

But sometimes it’s okay just to launch a tool and optimize as you go. 

Rhoback launched its AI agent two weeks before BFCM to automate routine tickets during the busy season. 

Why it worked:

  • Samantha had audited all of Rhoback’s SOPs, training materials, and FAQs a few months before implementation. 
  • They started by automating high-volume questions such as returns, exchanges, and order tracking.
  • They followed a structured AI implementation checklist. 

2. Audit your knowledge sources before you automate

Before turning on Rhoback’s AI Agent, Samantha’s team reviewed every FAQ, policy, and help article that human agents are trained on. This helped establish clear CX expectations that they could program into an AI Agent. 

Samantha also reviewed the most frequently asked questions and the ideal responses to each. Which ones needed an empathetic human touch and which ones required fast, accurate information?  

“AI tells you immediately when your data isn’t clean. If a product detail page says one thing and the help center says another, it shows up right away.” 

Rhoback’s pre-implementation audit checklist:

  • Review customer FAQs and the appropriate responses for each. 
  • Update outdated PDPs, Help Centre articles, policies, and other relevant documentation.
  • Establish workflows with Ecommerce and Product teams to align Macros, Guidance, and Help Center articles with product descriptions and website copy. 

Read more: How to Optimize Your Help Center for AI Agent

3. Train your AI Agent in small, clear steps

It’s often said that you should train your AI Agent like a brand-new employee. 

Samantha took it one step further and recommended treating AI like a toddler, with clear, patient, repetitive instructions. 

“The AI does not have a sense of good and bad. It’s going to say whatever you train it, so you need to break it down like you’re talking to a three-year-old that doesn’t know any different. Your directions should be so detailed that there is no room for error.”

Practical tips:

  • Use AI to build your AI Guidance, focusing on clear, detailed, simple instructions. 
  • Test each Guidance before adding new ones.
  • Treat the training process like an ongoing feedback loop, not a one-time upload.

Read more: How to Write Guidance with the “When, If, Then” Framework

4. Prioritize Tone of Voice to make AI feel natural

For Rhoback, an on-brand Tone of Voice was a non-negotiable. Samantha built a character study that shaped Rhoback’s AI Agent’s custom brand voice.

“I built out the character of Rhoback, how it talks, what age it feels like, what its personality is. If it does not sound like us, it is not worth implementing.”

Key questions to shape your AI Agent’s tone of voice:

  • How does the AI Agent speak? Friendly, funny, empathetic, etc…?
  • Does your AI Agent use emojis? How often?
  • Are there any terms or phrases the AI Agent should always or never say?

5. Use AI to surface knowledge gaps or inconsistencies

Once Samantha started testing the AI Agent, it quickly revealed misalignment between Rhoback’s teams. With such an extensive product catalog, AI showed that product details did not always match the Help Center or CX documentation. 

This made a case for stronger collaboration amongst the CX, Product, and Ecommerce teams to work towards their shared goal of prioritizing the customer. 

“It opened up conversations we were not having before. We all want the customer to be happy, from the moment they click on an ad to the moment they purchase to the moment they receive their order. AI Agent allowed us to see the areas we need to improve upon.” 

Tips to improve internal alignment:

  • Create regular syncs between CX, Product, Ecommerce, and Marketing teams.
  • Share AI summaries, QA insights, and trends to highlight recurring customer pain points.
  • Build a collaborative workflow for updating documents that gives each team visibility. 

6. Build trust (with your team and customers) through transparency 

Despite the benefits of AI for CX, there’s still trepidation. Agents are concerned that AI would replace them, while customers worry they won’t be able to reach a human. Both are valid concerns, but clearly communicating internally and externally can mitigate skepticism. 

At Rhoback, Samantha built internal trust by looping in key stakeholders throughout the testing process. “I showed my team that it is not replacing them. It’s meant to be a support that helps them be even more successful with what they’re already doing," Samantha explains.

On the customer side, Samantha trained their AI Agent to tell customers in the first message that it is an AI customer service assistant that will try to help them or pass them along to a human if it can’t. 

How Rhoback built AI confidence:

  • Positioned AI as a personal assistant for agents, not a replacement.
  • Let agents, other departments, and leadership test and shape the AI Agent experience early.
  • Told customers up front when automation was being used and made the path to a human clear and easy.

Read more: How CX Leaders are Actually Using AI: 6 Must-Know Lessons

Putting these into practice: Rhoback’s framework for an aligned AI implementation 

Here is Rhoback’s approach distilled into a simple framework you can apply.

  1. Audit your content: Ensure your FAQs, product data, policies, and all documentation are accurate.
  2. Start small: Automate one repetitive workflow, such as returns or tracking.
  3. Train iteratively: Add Guidance in small, testable batches.
  4. Prioritize tone: Make sure every AI reply sounds like your brand.
  5. Align teams: Use AI data to resolve cross-departmental inconsistencies and establish clearer communication lines.
  6. Be transparent: Tell both agents and customers how AI fits into the process.
  7. Refine regularly: Review, measure, and adjust on an ongoing basis.

Watch the full conversation with Samantha to learn how AI can act as a catalyst for better internal alignment. 

📌 Join us for episode 2 of AI in CX: Building a Conversational Commerce Strategy that Converts with Cornbread Hemp on December 16.

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min read.
Food & Beverage Self-Service

How Food & Beverage Brands Can Level Up Self-Service Before BFCM

Before the BFCM rush begins, we’re serving food & beverage CX teams seven easy self-serve upgrades to keep support tickets off their plate.
By Alexa Hertel
0 min read . By Alexa Hertel

TL;DR:

  • Most food & beverage support tickets during BFCM are predictable. Subscription cancellations, WISMO, and product questions make up the bulk—so prep answers ahead of time.
  • Proactive CX site updates can drastically cut down repetitive tickets. Add ingredient lists, cooking instructions, and clear refund policies to product pages and FAQs.
  • FAQ pages should go deep, not just broad. Answer hyper-specific questions like “Will this break my fast?” to help customers self-serve without hesitation.‍
  • Transparency about stock reduces confusion and cart abandonment. Show inventory levels, set up waitlists, and clearly state cancellation windows.

In 2024, Shopify merchants drove $11.5 billion in sales over Black Friday Cyber Monday. Now, BFCM is quickly approaching, with some brands and major retailers already hosting sales.

If you’re feeling late to prepare for the season or want to maximize the number of sales you’ll make, we’ll cover how food and beverage CX teams can serve up better self-serve resources for this year’s BFCM. 

Learn how to answer and deflect customers’ top questions before they’re escalated to your support team.

💡 Your guide to everything peak season → The Gorgias BFCM Hub

Handling BFCM as a food & beverage brand

During busy seasons like BFCM and beyond, staying on top of routine customer asks can be an extreme challenge. 

“Every founder thinks BFCM is the highest peak feeling of nervousness,” says Ron Shah, CEO and Co-founder of supplement brand Obvi. 

“It’s a tough week. So anything that makes our team’s life easier instantly means we can focus more on things that need the time,” he continues. 

Anticipating contact reasons and preparing methods (like automated responses, macros, and enabling an AI Agent) is something that can help. Below, find the top contact reasons for food and beverage companies in 2025. 

Top contact reasons in the food & beverage industry 

According to Gorgias proprietary data, the top reason customers reach out to brands in the food and beverage industry is to cancel a subscription (13%) followed by order status questions (9.1%).

Contact Reason

% of Tickets

🍽️ Subscription cancellation

13%

🚚 Order status (WISMO)

9.1%

❌ Order cancellation

6.5%

🥫 Product details

5.7%

🧃 Product availability

4.1%

⭐ Positive feedback

3.9%

7 ways to improve your self-serve resources before BFCM

  1. Add informative blurbs on product pages 
  2. Craft additional help center and FAQ articles 
  3. Automate responses with AI or Macros 
  4. Get specific about product availability
  5. Provide order cancellation and refund policies upfront
  6. Add how-to information
  7. Build resources to help with buying decisions 

1) Add informative blurbs on product pages

Because product detail queries represent 5.7% of contact reasons for the food and beverage industry, the more information you provide on your product pages, the better. 

Include things like calorie content, nutritional information, and all ingredients.  

For example, ready-to-heat meal company The Dinner Ladies includes a dropdown menu on each product page for further reading. Categories include serving instructions, a full ingredient list, allergens, nutritional information, and even a handy “size guide” that shows how many people the meal serves. 

The Dinner Ladies product page showing parmesan biscuits with tapenade and mascarpone.
The Dinner Ladies includes a drop down menu full of key information on its product pages. The Dinner Ladies

2) Craft additional Help Center and FAQ articles

FAQ pages make up the information hub of your website. They exist to provide customers with a way to get their questions answered without reaching out to you.   

This includes information like how food should be stored, how long its shelf life is, delivery range, and serving instructions. FAQs can even direct customers toward finding out where their order is and what its status is. 

Graphic listing benefits of FAQ pages including saving time and improving SEO.

In the context of BFCM, FAQs are all about deflecting repetitive questions away from your team and assisting shoppers in finding what they need faster. 

That’s the strategy for German supplement brand mybacs. 

“Our focus is to improve automations to make it easier for customers to self-handle their requests. This goes hand in hand with making our FAQs more comprehensive to give customers all the information they need,” says Alexander Grassmann, its Co-Founder & COO.

As you contemplate what to add to your FAQ page, remember that more information is usually better. That’s the approach Everyday Dose takes, answering even hyper-specific questions like, “Will it break my fast?” or “Do I have to use milk?”

Everyday Dose FAQ page showing product, payments, and subscription question categories.
Everyday Dose has an extensive FAQ page that guides shoppers through top questions and answers. Everyday Dose

While the FAQs you choose to add will be specific to your products, peruse the top-notch food and bev FAQ pages below. 

Time for some FAQ inspo:

3) Automate responses with AI or macros

AI Agents and AI-powered Shopping Assistants are easy to set up and are extremely effective in handling customer interactions––especially during BFCM.  

“I told our team we were going to onboard Gorgias AI Agent for BFCM, so a good portion of tickets would be handled automatically,” says Ron Shah, CEO and Co-founder at Obvi. “There was a huge sigh of relief knowing that customers were going to be taken care of.” 

And, they’re getting smarter. AI Agent’s CSAT is just 0.6 points shy of human agents’ average CSAT score. 

Obvi homepage promoting Black Friday sale with 50% off and chat support window open.
Obvi 

Here are the specific responses and use cases we recommend automating: 

  • WISMO (where is my order) inquiries 
  • Product related questions 
  • Returns 
  • Order issues
  • Cancellations 
  • Discounts, including BFCM related 
  • Customer feedback
  • Account management
  • Collaboration requests 
  • Rerouting complex queries

Get your checklist here: How to prep for peak season: BFCM automation checklist

4) Get specific about product availability

With high price reductions often comes faster-than-usual sell out times. By offering transparency around item quantities, you can avoid frustrated or upset customers. 

For example, you could show how many items are left under a certain threshold (e.g. “Only 10 items left”), or, like Rebel Cheese does, mention whether items have sold out in the past.  

Rebel Cheese product page for Thanksgiving Cheeseboard Classics featuring six vegan cheeses on wood board.
Rebel Cheese warns shoppers that its Thanksgiving cheese board has sold out 3x already. Rebel Cheese  

You could also set up presales, give people the option to add themselves to a waitlist, and provide early access to VIP shoppers. 

5) Provide order cancellation and refund policies upfront 

Give shoppers a heads up whether they’ll be able to cancel an order once placed, and what your refund policies are. 

For example, cookware brand Misen follows its order confirmation email with a “change or cancel within one hour” email that provides a handy link to do so. 

Misen order confirmation email with link to change or cancel within one hour of checkout.
Cookware brand Misen follows up its order confirmation email with the option to edit within one hour. Misen 

Your refund policies and order cancellations should live within an FAQ and in the footer of your website. 

6) Add how-to information 

Include how-to information on your website within your FAQs, on your blog, or as a standalone webpage. That might be sharing how to use a product, how to cook with it, or how to prepare it. This can prevent customers from asking questions like, “how do you use this?” or “how do I cook this?” or “what can I use this with?” etc. 

For example, Purity Coffee created a full brewing guide with illustrations:

Purity Coffee brewing guide showing home drip and commercial batch brewer illustrations.
Purity Coffee has an extensive brewing guide on its website. Purity Coffee

Similarly, for its unique preseasoned carbon steel pan, Misen lists out care instructions: 

Butter melting in a seasoned carbon steel pan on a gas stove.
Misen 

And for those who want to understand the level of prep and cooking time involved, The Dinner Ladies feature cooking instructions on each product page. 

The Dinner Ladies product page featuring duck sausage rolls with cherry and plum dipping sauce.
The Dinner Ladies feature a how to cook section on product pages. The Dinner Ladies 

7) Build resources to help with buying decisions 

Interactive quizzes, buying guides, and gift guides can help ensure shoppers choose the right items for them––without contacting you first. 

For example, Trade Coffee Co created a quiz to help first timers find their perfect coffee match: 

Trade Coffee Co offers an interactive quiz to lead shoppers to their perfect coffee match. Trade Coffee Co

Set your team up for BFCM success with Gorgias 

The more information you can share with customers upfront, the better. That will leave your team time to tackle the heady stuff. 

If you’re looking for an AI-assist this season, check out Gorgias’s suite of products like AI Agent and Shopping Assistant. 

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min read.
Call to action
Create powerful self-service resources
Capture support-generated revenue
Automate repetitive tasks

Further reading

Shopify Plus Pricing Cost

Understanding Shopify Plus Pricing & Cost

By
12 min read.
0 min read . By

Without a doubt, Shopify is one of the most popular e-commerce platforms. Entrepreneur magazine ranks it as one of the Top 6 Ecommerce Platforms for Small Businesses. And Inc. Magazine ranks Shopify in their list of Top Seven E-Commerce Platforms. What’s more, Market Watch calls Shopify “the leading multi-channel commerce platform”.


Headquartered in Ottawa, Ontario, Shopify is an e-commerce platform for both online stores and retail POS (point-of-sale) systems. Shopify describes itself as “One platform with all the ecommerce and point of sale features you need to start, run, and grow your business.”


According to Shopify, more than 800,000 businesses in 175 countries use its e-commerce platform. For the calendar year 2018, the platform’s total gross merchandise volume exceeded $41.1 billion. In a recent earnings forecast, Shopify expects 2019 revenue to be between $1.48 billion and $1.50 billion.


Out of the box, Shopify offers a low threshold for entry and is easy to set up and use. Shopify offers several basic plans and pricing models for a variety of business types and sizes. Their entry pricing model serves as an excellent example for current and future startups to emulate.


However, for more robust businesses and existing enterprises looking to migrate to a new e-commerce platform, there is Shopify Plus. Launched in 2014 the Plus option is geared towards enterprise level businesses. As a result, it is more robust. In this article, we’ll explore Shopify Plus, look at Shopify Plus pricing, and compare it to a few other e-commerce platforms.


Advantages of Shopify Plus

While Shopify is adequate for your average e-commerce outfit, larger enterprises have more extensive c-commerce needs. Consequently, these companies need better-than-average solutions. As a result, many flagship brands, including Kylie Jenner, Red Bull, and others, use Shopify Plus.


Even though all of Shopify’s options (including Shopify Plus) use the same dashboard, editor, and help center, Shopify Plus offers these enterprise-level companies much more functionality than any of Shopify’s other plans.


For example, Shopify Plus comes with unlimited staff accounts along with personalized help and support. On top of that, it can handle over 10,000 transactions per minute. This means that large-volume retailers don’t need to worry about whether their site will crash. Marketing educator, consultant, and SEO specialist Nate Shivar lists a several of Shopify Plus’ other main advantages.


  • Scaling Reliability — Proven infrastructure which supports enterprise-level businesses or business’ scaling up to that enterprise level; also beneficial for retailers who need seasonal scaling to accommodate increased holiday traffic
  • International Deployment — Built-in tools like geo-targeting, currency, and language options to easily and quickly expand internationally
  • APIs, Integration & Extensions — Add-on friendly and easily extensible with its own App Store ecosystem
  • Predictable Pricing — Starts at $2,000 per month, which includes a lot of beneficial services:
  • Development and Maintenance — Includes hosting, servers, bug fixes, order management, bandwidth, feature implementation, and file storage are all part of the platform
  • Technical Support and Account Management — Dedicated account manager for each client
  • Marketing — Includes many standard marketing tools


All of these features make Shopify Plus an ideal option for launching an e-commerce site or adding e-commerce options to existing sites.

Check out our in-depth post of the benefits of Shopify Plus for more information.

The Base Costs of a Shopify Plus License

As stated above, the Shopify Plus annual licensing fee starts at $2,000 per month. So you could plan on spending at least $24,000 per year on the license alone. In addition, you will spend an extra percentage depending on your revenue. Since Shopify Plus bases pricing on usage and sales volume, the license cost increases when you exceed $800k in a month.


On top of the basis licensing fee, Shopify Plus also has a fee structure based on revenues. This is the actual pricing of the platform. There is a ceiling to this pricing — the maximum license fee is $40,000 monthly. For example, according to Shopify Plus pricing, a $1,000,000 per month company pays $2,500 in monthly licensing fees. In order for that same merchant to pay the maximum $40,000 monthly license fee, they would need to reach $16 million in monthly sales.


So what does $2,000 a month buy you on the Shopify Plus platform? This monthly license covers a number of services, including:


  • Hosting Fees
  • Maintenance Costs
  • Version Upgrades
  • Native Multi-channel Capabilities
  • Shopify’s POS solution — along with integrated selling solutions for eBay, Facebook, and Amazon
  • Account Management — including a dedicated Launch Manager and Account Manager who typically provides:
  • General Shopify support and suggestions
  • About 3 hours per month of basic front-end development work
  • Guidance for growing your store
  • Onboarding support
  • General Shopify Plus solutions advice


Overall, the Shopify Plus pricing structure is competitive. Especially considering that this cost includes hosting. Specifically, this pricing positions the platform on the lower end for enterprise-level e-commerce solutions.


But what if you already have an e-commerce presence? Can you migrate to Shopify Plus? The short answer is ‘Yes’. If your business already has an online store, but have thought of switching to a new platform, then this Shopify Plus pricing guide is perfect for you. This guide won’t dive into the technicalities of migration, but it will mainly focus on options and pricing.


Moving an Existing E-commerce Site to Shopify Plus

An increasing number of retailers have chosen to move to Shopify Plus including MVMT, Gymshark, Hawkers, puravida, and Emma Bridgewater. Of course the Shopify Plus website touts all the platform’s features, benefits, and perks. However, Shopify does not explicitly list the cost of migrating your site from your current e-commerce platform to Shopify Plus.


In general, the lack or standard pricing for moving your site to Shopify Plus is mainly because each business is unique. Specifically, Shopify Plus asks you to contact them, so they can walk you through the process, plans, and pricing.  This makes sense, especially considering that your specific Shopify Plus pricing depends on several factors including scale, revenue, traffic, and others.

Side Costs of Shopify Plus

Although Shopify doesn’t outline the side costs of migration, at the same time, there are some sample prices from third-parties that serve as solid guidelines. Based on a hypothetical mid-level Shopify Plus project, we’ve outlined some more specific pricing for a mid-level enterprise’s first year of using Shopify Plus. Overall, a mid-level user could expect to spend between $130,200 and $270,200 during their first year with Shopify Plus. Below is a cost breakdown:


  • $60,000 to $200,000 — The average build cost for a Shopify Plus site; depends on the scope of the project and complexity of the site
  • $24,000 annually — Annual Shopify Plus licensing cost, starting at $2000 per month; this increases based on your revenue level
  • $36,000 annually — BAU development costs
  • $7,200 annually- Third party services for shipping, personalization, search, etc.
  • $3,000 annually (about $250 per month) — Average yearly app costs

Factoring in Costs for Shopify Apps

Shopify Plus has a great deal of functionality. At the same time, third-party apps boost and extend its capacity even further. These apps meet needs like enhanced SEO tools, enterprise-level functionality, and enhanced site personalization. As a result, when talking about Shopify Plus pricing, be aware that you’ll need to spend money on additional apps for improved functionality of your e-commerce site.

In general, the norm for Shopify Plus third-party apps to pay a monthly licensing fee. One of the great benefits of this pricing model is the low cost of entry. Yet at the same time, paying a monthly fee for numerous apps tends to add up. If you are accustomed to Magento, which generally offers one-off license fees for apps, this will require an adjustment to your budgeting.

So even though you’ll spend less money up front, your total monthly costs for Shopify Plus apps may be more than you’re accustomed to. What’s more, apps have different monthly costs — licensing fees for Shopify Plus apps range from $50 to $500 each. However, one major benefit of monthly app licenses is that if you don’t like an app or find you don’t need it, you simply stop using it and find another app.

Be aware that if your business requires a specialized, custom-made app, then you’ll pay a premium for it. For example, development firms tend to charge $90 to $175 per hour for built-from-scratch apps. So the actual cost of the app will depend on its complexity, function, and size.

Related: Our list of the best Shopify apps for ecommerce merchants.

Site Design and Build Costs

Regarding site design and build, Shopify Plus does offer templates you to purchase. Yet if you choose a template, you’ll inevitably want to personalize it to differentiate your site from all the other e-commerce sites out there. This means you’ll pay for personalization, either in the form of a tailor-made site or a heavily-modified template.


Whether you do this design and build work in-house or contract with a design firm or a freelancer, it is important to factor in this cost. Depending on your needs, the estimated cost for this service might range between $75,000 and $100,000 (or more). And of course, the actual cost hinges on the complexity of your site and your business’ specific needs. Larger merchants with more complex needs will spend considerably more during the design and build process.


When migrating your site to Shopify Plus, make sure you work with a firm or freelancer who specializes in this platform. Overall, the firm you choose should be both creative and practical. This means they should deliver a unique, attractive, user-friendly site which also delivers exceptional functionality on every level.


Because of this, finding the right agency to build your site is key to success. Consider working with a Shopify Plus Technology partner to ensure you get the build possible.

Payment Processing Costs Via Shopify Payments

On top of the licensing fees, every merchant pays payment processing costs to a payment processor. This is true whether you use Shopify Payments or third-party processor. At the same time, you might find lower charges by using a third-party payment processor. In addition, be aware that Shopify does charge a 0.15% fee if you use a third-party payment provider.

Shopify Plus Pricing Compared to Other Platforms

How does Shopify Plus pricing stack up to other e-commerce platforms? Below we examine a few of the most popular platforms and compare them to Shopify Plus:

Shopify Plus vs Shopify


When talking about Shopify Plus, it’s helpful to introduce regular Shopify. With this plan, you get a 14-day free trial period without any up-front setup fees. Simply you can jump in and set up your store while you decide which pricing plan best fits your needs. There are three monthly pricing options:


  • Basic Shopify (for starting your new business) - $29 per month
  • Shopify (for growing your business) - $79 per month
  • Advanced Shopify (for scaling your business) - $299 per month


Each of these plans comes with different options and levels of service for your business. All three come with an online store, sales channels, 24/7 customer support, unlimited products, the Shopify POS app, and other features. Yet, as you can imagine, the more you pay, the more options you get for your business.


For example, the Basic plan includes 2 Staff Accounts while the Shopify and Advanced Shopify include 5 and 15 Staff Accounts respectively. In addition, Advanced Shopify has exclusive features like an Advanced Report Builder and Third-party Calculated Shipping Rates. However, Shopify Plus definitely has even more to offer.

Read our in-depth comparison of Shopify and Shopify Plus.

Shopify Plus vs Magento 2 Commerce

First released in 2008 by Varien, Inc, Magento is an open-source platform. Written in PHP, Varien originally developed this e-commerce software with the help of volunteers. Varien released the first general-availability version of Magento on March 31, 2008. After changing hands a couple of times, Adobe later acquired the platform. On November 17, 2015, Magento 2.0 was released.


Overall, Shopify Plus is less expensive than Magento 2 Commerce. According to Ecommerce Guide:


The ‘Total Cost of Ownership’ of a website built on Shopify Plus tends to be cheaper than a site built on Magento 2 Commerce.


The site also suggests that this lower cost makes Shopify Plus a better option for businesses that are currently at lower revenue levels. The article also details a few other costs comparisons between Shopify Plus and Magento:


  • Design/ Build Costs — Magento Commerce builds tend to cost more than Shopify Plus projects. One reason for Shopify Plus’ lower build cost is that the builds involve less integration work and less backend development. In the end, less time working on the build means you spend less money up front. Specifically, Ecommerce Guide estimates spending about $100,000 for a Shopify Plus build and between $150,000 to $500,000 for a Magento 2 Commerce build.
  • License Fees — Although both Shopify Plus and Magento 2 Commerce come with a license fee, Shopify Plus charges on a monthly fee while Magento charges an upfront, annual license fee. As is the case with Shopify Plus, Magento also bases the fee on your business’ revenue level. However, Magento bills you up front annually as ‘Gross Merchandise Value’. So for Magento Commerce licensing fees, expect to pay about $2,000 per month if you’re at the lowest monthly level fee.
  • Hosting — As stated above, the $2,000 per month Shopify Plus license fee includes hosting. Shopify Plus hosting includes security patches, SSL certificates, PCI compliance, and other things. In comparison, Magento offers two options. Magento 2 Commerce Cloud has a similar hosting package but at a slightly higher monthly fee. Magento’s base cost is around $3,333 which includes the license and hosting.
  • Site Maintenance — For monthly maintenance, fixes, and updates, Shopify Plus is typically cheaper than Magento.


At the end of the day, Shopify Plus is generally less expensive than Magento 2 Commerce. At the same time it depends on your business’ specific needs.

Shopify Plus vs WooCommerce

For small to large-sized online merchants that use WordPress, WooCommerce is a popular open-source e-commerce plugin. Designed specifically for WordPress, it launched September 27, 2011. The fact that the plugin is free (the base product) easy install makes it an attractive to businesses of a certain size.


In a comparison article, Simon Gondeck puts Shopify Plus up against Woo Commerce. He bases his comparison on several factors. Gondeck uses the example of a lower mid-market ecommerce business making between $1 million and $10 million in annual sales.


For a Shopify Plus site, he estimates the build cost (design and development) to be around $30,000. The monthly license fee is $2,000 per month, but Gondeck adds an estimated $2,000 per month for ‘developer maintenance costs’. At the end of the first year, he estimates the cost for a Shopify Plus site to be about $78,000. However, once the site is fully developed, the second year cost would drop to an estimated $48,000 per year.


For WooCommerce, Gondeck estimates the build cost to be about the same as Shopify Plus (around $30,000). However, he believes WooCommerce has lower month to month maintenance fees and costs. Although the developer maintenance costs are similar (about $2,000 per month), the monthly license fee (which includes the domain and hosting costs) is only about $200 per month. With all the costs totaled up, WooCommerce comes in at around $55,200 for the first year with an ongoing annual cost of about $26,400 per year.


Yet in the end, Shopify Plus pricing comes out slightly higher than WooCommerce in a head-to-head comparison. Gondeck recommends Shopify Plus for its simplicity and ease of use out of the box. He specifically recommends this e-commerce platform “for larger businesses with no current ecommerce presence.”

Shopify Plus vs BigCommerce Enterprise

Founded in 2009, BigCommerce develops e-commerce software for businesses. According to the company, the BigCommerce platform has processed $16 billion in total sales.


Like Shopify, BigCommerce has also launched an enterprise-level platform, BigCommerce Enterprise. Launched in May 2015, the platform was designed to accommodate high-volume retailers. And like Shopify Plus, BigCommerce also hosts some big name brands such as Skullcandy and Ford. So how does Shopify Plus pricing compare to BigCommerce Enterprise?


As we’ve already said a couple of times, Shopify Plus pricing starts at $2,000 per month with increases based on your sales volume. Also, Shopify Plus has no hosting fees, support fees, or monthly maintenance costs. In contrast, BigCommerce Enterprise’ pricing various greatly. Like Shopify Plus, BigCommerce doesn’t explicitly list prices for the Enterprise platform. However, according to WebMakeWebsites, you can get a basic plan for around $400 per month.


However, Nate Shivar puts the BigCommerce Enterprise’s monthly price at around $1,000. Yet, depending on your business’ capacity and needs, the high end of the monthly fee can add up to $15,000 per month. In the end, Paul Rogers states:


The pricing of Shopify Plus and BigCommerce generally comes out very similar — the licensing is comparable (with BigCommerce Enterprise being based on order volume and Shopify Plus being a GMV model with a minimum fee) and build costs are generally in the $75k – $200k bracket for both, in my experience. Shopify Plus does have some additional charges if you choose to use an external payment provider, but this is relatively low (0.25%).


Like Shopify Plus pricing, your actual BigCommerce pricing monthly depends on your sales, traffic, and other factors.

In Conclusion: Advantages of Shopify Plus

Without a doubt, Shopify is one of the top e-commerce platforms available today. And with Shopify Plus, enterprise-level businesses benefit from exceptional functionality to meet all their e-commerce needs. Compared to popular platforms like Magento, WooCommerce, and BigCommerce, Shopify Plus is a great platform for new e-commerce sites or for companies looking to migrate to a more robust platform. So whether you’re already at the enterprise level or you have plans to scale up to the next level like Campus Protein, Shopify Plus is certainly one of your best e-commerce options.

Still on the fence? Read our in-depth review of Shopify Plus.


Gorgias is a customer support helpdesk providing flawless customer service for Shopify stores. Currently, we partner with over 1,000 merchants and our Starter plan is only $10/month. Get started for free or schedule a demo today! Or Contact Us Today to learn more about what we can do for your Shopify site.

Shopify
Marginal Cost of Customer Support

How to Calculate the Marginal Cost of Customer Service

By Derric Haynie
3 min read.
0 min read . By Derric Haynie

And the Margin that Customer Service Impacts Your Net Profit.

In, The State of the Ecommerce Customer Service Industry Report for 2019, we found that a surprising 79% of respondents do not know the cost of a support ticket on the company.

This is quite scary, as this metric helps define the overall profitability of the product, and set reinvestment schedules for the growth of your company.

If costs overtake margin, you lose money with every sale.

While the Gorgias mission is to turn customer service from a cost center into a revenue generator, we do need to acknowledge the raw costs of customer support in order to bake it into our calculation of margin.

What metrics are we going to cover:

  • Cost per support ticket.
  • Cost per order.
  • Cost per revenue.

Why should you track these metric?

  • It helps baseline your opportunity for growth and profitability.
  • You can make concerted efforts to lower your cost with customer service improvements.
  • You can track indicators that something is going wrong with your business, and may require extra attention from the Head of Ecommerce or COO.
  • You can hold your head of customer service accountable for staying within appropriate margins, and incentivize them accordingly.

Now, let’s get into it…

Step 1: Calculate your Cost Per Ticket

Here’s the data you need to collect:

Total cost of customer service. This includes technology, employees, managers, office space, equipment, travel… Everything. This should be easy to calculate if your accounting department is doing their job; they should be able to just hand you over a number. A monthly breakdown of the trailing 12 months is best.

Tickets per month. This can be found in your Gorgias dashboard under “Statistics.

Be sure to set the dates to match appropriately:

Now that we have these two numbers, we can get an understanding of our cost per support ticket.

Simply divide: In this example, we’ve got 1651 tickets in December. We spent ~$4500 on customer service. Therefore each ticket costs us $2.73.

Knowing your average cost per ticket helps you understand the time and value behind resolving customer inquiries. If this number goes up, then you’re inquiries are getting more complex - its either taking more time or more people to answer the same number of questions.

If you ever see this number spike, it’s likely due to a flaw in your product design. Immediately begin looking for commonalities among tickets, inspecting your inventory, and trying to get to the root of the problem before you make even more customers unhappy.

‍

Step 2: Calculate Your Support Cost Per Order

Next up, you need to know your support cost per order, in order to bake customer support into your margin.

Here’s the data you need to collect:

  • ‍Orders per month.

To find this, simply log in to your Shopify dashboard, go to Orders, and add in a couple filters:

You can then “select all” and it will tell you the count of orders. For additional accuracy, you may want completed orders, not including refunds or other issues.

For our example month, we placed 2621 orders. That gives us a cost per order of $1.73

According to our Ecommerce Customer Service data, we estimate that small stores will see 88 support tickets per 100 orders, or roughly 1.1 support tickets for every $100 in revenue.

While large stores, with over $500k revenue/month, will see only 56 support tickets per month and .4 support tickets per every $100 in revenue.

How does your support cost per order compare with these benchmarks? Let us know in the comments below.

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Calculate Your Cost Per Revenue

Sometimes it's helpful to calculate your cost per revenue as well, which is simply grabbing your net sales number from Shopify and dividing by tickets.

Data you need to collect:

Revenue.

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Step 3: Consult with COO / Head of Ecommerce

You were previously calculating your margin without including the cost of support…

Even though support drives customer satisfaction, retention, and, in some cases, sales, it also has a clear impact on margin.

How does this new metric affect your COGS? Your margin?

If your average order value is $50, with a $13 margin, you now have only a $11.27 margin.

How does that affect your advertising objectives?

How does it affect your ability to invest into product research?

What can you do to improve your cost per order?

A lot. Mostly, this is called: ticket mitigation.

Here’s some of the more common opportunities:

  • Updating your FAQ page.
  • Improving your product detail pages.
  • Video explainers.
  • Onboarding videos.
  • Educational retargeting campaigns,
  • Stricter / more clear checkout processes.
  • Improved notification emails to users.
  • Faster shipping.
  • Implementing new channels like SMS, on-site chat, or phone.



Final Thoughts

When you hire a new support agent, or manager, you will see your costs go up.

This is the nature of business: you’re investing in a new hire with the expectation that there will be more demand for them to fulfil.

You’re job, as an operations manager, head of Ecommerce, or COO, is to make sure those costs don’t get out of control while you look to scale your business.

Figure out what margins are acceptable to you and invest in growth cautiously. We’ve seen all too many companies fail because they oversupply and hit stretches of low demand.

That being said, if the business has healthy cashflow, and reasonable growth, I’d invest more in customer service before upping my ad budget.

It takes time to onboard new agents, and if you don’t have someone matching that demand, you’re creating unhappy customers, which is a surefire way to eat your margins even faster.

Customer Service Team Management
Reduce Customer Support Load

3 Ways to Reduce the Load On Your Customer Support Team

By Ross Beyeler
8 min read.
0 min read . By Ross Beyeler

‍By Ross Beyeler, Founder and CEO of Growth Spark


Often, a support team answers the same questions over and over…


Or issues returns repeatedly for reasons that could be addressed internally…


Maybe the sizing isn’t well represented, the fulfillment house has mixed up SKUs, or your product images aren’t clear or detailed enough.


If you can lighten the load for your customer support team, you can save significant time and costs, while at the same time improving the buying experience for your customers.


The goals here are to:


  • Reduce repeat inquiries
  • Shorten first response times
  • Speed up problem resolution time
  • Lower overall customer care costs


The key is to address your customers questions and issues before they ask your support team. Here's how you do that:


A Better FAQ Page


91% of shoppers would gladly try to answer their own questions first using an online knowledge base or FAQ page before reaching out to a customer service team, according to a survey by Coleman Parkes for Amdocs.


This means that your FAQ page is a huge opportunity to answer your customers’ most common questions and issues so they don’t need to reach out to customer support.


FAQ information typically falls into one of two distinct buckets: product-specific and buying process.


Product Specific: Common questions about individual products may be better off addressed on the product pages rather than in a broad FAQ page. You may need to provide clearer or more comprehensive product descriptions, or consider more or better photography to clear up common product questions.


Buying Process: Questions about shipping, returns, policies, and other operational topics are best addressed in a single easy-to-find page like an FAQ.


When is the last time you cross-checked the content of your FAQ page with the data from your customer support team?


There are many customer support tools like Gorgias that will make it easy for you to track the reasons behind why users submit a ticket.


Once you begin tracking the topic, or tag, of your questions, you can easily identify the questions that top the list, and permanently add the responses to the FAQ.


Bonus points: Prioritize the FAQ page based on the frequency of each customer service inquiry so that the most relevant answers are closer to the top.


Your next step is to set up a monthly meeting with your head of customer service to review the feedback coming in from your customers and ask yourself:


  • What are the most frequent topics of support inquiries?
  • What issues take up the majority of your support team’s time and resources?
  • What issues are emerging or could emerge do to seasonality or new initiatives within our company?


Remember, an FAQ page is:


  • Easy to find
  • If shoppers can’t find it quickly and easily, they won’t use it and all your work answering all of their questions will go to waste. If you have an answer on your FAQ page, yet people are still inquiring, they might be having trouble finding the page.


  • Searchable
  • Include a search bar so that shoppers can easily find the answers for their specific problem without having to read through everything else.


  • Easy to read
  • Use simple, conversational language. Technical slang gives most of us a headache, and leaves most people reaching for the closest live human to explain it in terms they understand.


For more on FAQ pages, check out this Shopify article.


Now that you have your FAQ page squared away, be sure to track visitors to the page and note any changes in volume, and look for changes in your support ticket volume around those related questions.


Remember: You should never answer a support ticket only by referencing your FAQ page. Always include the information they are asking for directly within your response. After that, let the customer know that there is an FAQ page for more information, to avoid future tickets.


See Where Your Customers Get Tripped Up


Have you watched actual customers explore your online store to see where they stumble?


Customer behavior tools like Hotjar make it easy to review how customers navigate your website. One way that customer behavior analysis tools can help you understand exactly how your customers are using your site is with heat maps.


image


A heat map is a visual representation of the most popular (hot) and unpopular (cold) elements of a website page. They can give you an at-a-glance understanding of how people interact with individual website pages. Elements that get the most views and interaction are shown in red, so you can immediately spot what your users are clicking on. Those that most people tend to ignore appear in blue.


Once you know which parts of your website are most (and least) useful to shoppers, you can tweak those elements to make the on-site experience easier to use.


Customer behavior data can inform on-site improvements, such as:


  • Identifying any “dead” pages so you can remove them
  • Recognizing “deep” content that requires too many clicks for customers to reach, and making it more visible or accessible
  • Ensuring that customers can easily see and access main links, buttons, and CTAs
  • Making sure that important elements are getting the attention they deserve
  • Checking whether any static elements are getting clicked too often, and adjusting them to clarify that they aren’t a linked object


It may require some A/B testing to ensure your changes deliver results.


Learn from Returns


According to a recent Shopify post, during the holiday season, Ecommerce returns surge to 30 percent (or as high as 50 percent for “expensive” products).


Return deliveries are estimated to exceed $550 billion by 2020 in the U.S. alone.


Many of those returns are probably associated with a customer support ticket - whether customers are asking questions about the product they received, or need help processing their return.


Anything you can do to reduce the number of returns - and the number of customer support requests associated with them - can mean a huge boost for your bottom line.


So, what causes returns?


Returns can often be traced back to a disconnect between customer expectations and the reality of the product once they receive it. It may be that:


  • It doesn’t fit the way they expected
  • It doesn’t look or feel like they thought it would
  • Delivery came later than they expected (or not at all)


All of these problems (and more) can be prevented in advance with improvements to your website content.




Sizing Issues

While fit can be a difficult factor to get right online, including detailed dimensions is a big step in the right direction. Some apparel merchants are taking sizing one step further with interactive fit guides, like the one above Nudie Jeans, which uses an app integration called Virtusize:.

image


Appearance Issues

Poor quality or not enough product images can make it difficult for customers to accurately understand what your product will look like when it arrives at their home.


You can easily reduce your return rate by making sure your product photography is clear and high-quality, and illustrates all of the primary parts of each product. More complicated or detailed products can also benefit from a video or 360-view.


Detailed product descriptions can also help address confusion about product appearance and feel. Sol de Janeiro does this with a multi-tab product content area that defaults to a brief product highlight, with additional tabs to provide more details.


image



Fulfillment Issues

Are orders not being fulfilled to the right customers?


Are deliveries taking longer than they should?


Analyzing your fulfillment data and using that information to make adjustments to your website content - such as average delivery times - can help eliminate a source of customer support calls.


image


For example, maybe you want to be able to deliver every order within two days, but your current fulfillment resources simply can’t make that happen consistently. Being up-front and clear about realistic delivery times (like The Black Dog does in their Shipping FAQ page, above) will help set customers’ expectations appropriately.


Bonus: To get setup on two day shipping, consider our partners at ShipBob.


Final Thoughts


Continue to study your on-site data using Google Analytics or Shopify’s native analytics and look for high exit % pages. These may be pages where prospects or customers are running into a dead end and being forced to turn to support.


You can also create a goal in Google Analytics that corresponds to contacting support, then reverse the user path to determine which pages lead to them submitting a ticket / hitting that “contact” or “support” button.


Chances are, there are a few areas of “low hanging fruit” that can make significant improvements to your customer support load once you find them and address the root concerns. And with those small fixes, you could see a big impact on your bottom line, and a better on-site experience for your customers.


Read more about customer support on our trusted partner’s site, Growth Spark:


Best Practices for Shopify E-Commerce Customer Service

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Customer Loyalty Ecommerce

Customer Loyalty: Bringing The Human Touch Back To Ecommerce

By Mollie Woolnough-Rai
3 min read.
0 min read . By Mollie Woolnough-Rai

Ecommerce has become awash with digital bells and whistles. Technology has no doubt enhanced the shopper experience but the rapid rate of digital innovation has had a profound effect on customer expectations. By 2020, customers expect brands to automatically personalize experiences to address (not just predict) their current – and future – needs.

But, although customers expect more in terms of tech, they still crave the person-to-person connection. In fact, 75% of consumers want to see more human interaction, not less.

At LoyaltyLion we know that bringing back this human-touch depends on providing a good customer experience. Clearly, a worthwhile cause, as studies show that 86% of shoppers who received great customer care are more likely to repeat purchase. By going the extra mile to treat your shoppers as people – rather than numbers – you can secure a faithful, constant customer base.

Here are three insights that will help you bring the human touch back to your online store.

Use Data To Personalize Communications

Each customer is unique. They interact with your brand in different ways, all while having their own personal needs and desires. When a customer feels that you have taken the time to understand their unique requirements, they will trust and value your brand more.

Data and personalization go hand in hand. By using member information to learn how customers engage with your loyalty program, you can understand their feelings towards your brand and react accordingly. Being data-driven is the key to true e-commerce success.

One golden opportunity to personalize your communications this is through targeted emails. Use your Gorgias dashboard to identify past interactions and purchases, as well as a customer’s loyalty points balance. You can then use that member data to create bespoke rewards that you can send right to your customer’s inbox.

Maybe you’ve noticed that they keep eyeing a specific product range? If so, give them discounts on new products in that collection to tempt them to back to buy again. Or perhaps you’re aware that they’re just a couple of points away from their next reward. Give them a little nudge to return and receive their reward sooner. For example, LoyaltyLion user Dr. Axe alerts customers when they have rewards waiting to be claimed, and suggests a particular product to redeem that reward on.

Find Ways To Delight Customers

Shoppers love to feel that they’re your only priority and that you care about them on a personal level. They want to feel valued as individuals, not just another number in an extensive database.

Loyalty strategies should incorporate ways to surprise and delight customers. For example, making it easy to offer customers points on their birthday or taking a moment to personally congratulate them when they’ve made a certain number of purchases with you. Beauty Bakerie, for example, offers their customers 500 points on their birthday.

With Connectors for Shopify Flow, it’s easy to use LoyaltyLion and Gorgias to set up triggers that automatically create tickets on a customer’s birthday, reminding a representative to get in touch. It’s the thought that counts and going the extra mile will ensure your customers trust and remember you. Plus, you’ll feel good about it too!

Convert Negative Experiences Into Positive Ones

Customers get frustrated when they feel their complaints aren’t taken seriously. Dissatisfied customers will tell between nine and 15 people if they have a bad brand experience. Using Gorgias’ helpdesk and macros, you can help resolve complaints whilst maintaining a personal touch. For example, ethical online yarn store, Darn Good Yarn uses the helpdesk to analyse and automate how they solve common customer issues, using a whole database of the shopper’s history to address specific queries in a more informed way.

If you are reacting to customers have had a negative experience, your loyalty program can help you demonstrate you care. You might consider offering bonus points or benefits such as free delivery, or moving them up a loyalty tier so that they can unlock more exclusive rewards in the future. These tokens of appreciation can turn a bitter experience into a sweet deal.

Research shows that 94% of customers who have their issues solved painlessly said they would purchase from that company again. This shows that helping customers to solve their problems is key to securing their long-term loyalty. Treat your most valuable customers well by making their shopping experiences as easy as possible. In return, they’ll give you their loyalty.

It’s all about people-to-people

In a world where technology and data can give ecommerce stores a competitive edge, there’s a risk that we could lose touch with the human side of retailing. Human exchanges are still, and always will be, the primary driver of loyalty. So, use digital personalization to your advantage and treat your customers as individuals.  

Customer Experience
Ecommerce Growth
Small Engineering Team As A Competitive Advantage

Small engineering team as a competitive advantage

By
6 min read.
0 min read . By

It's been over 3 years since we've started working on the Gorgias helpdesk. The engineering team started with just me (Alex) and then gradually grew to a team of 5 people. We're a small team, but we've accomplished a lot during this period. Here are some stats from 0 code/customers/revenue in Oct 2015 to this:

  • Handled over 16 million tickets.
  • 2000 daily active sessions with an average length of ~4h each.
  • 600 paying customers (companies).
  • 17% MoM revenue growth.

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Modest numbers to be sure, but we're very proud that people use our product in a big part of their workday and hopefully are becoming more productive while doing so. The whole idea behind our product is to scale customer support with as little resources as possible. Given this, perhaps it's only natural to build our product with a small team as well?

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We've been suffering chronically from "not having enough people" - we still do. That forced us to adopt a certain engineering culture that I want to talk about in this post.

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When we first started building Gorgias, having just a few people on the team allowed us to progress at a pace where we could collect real feedback from our customers with things that really mattered to them rather than building every feature they ask for. A lot of their asks seemed legitimate, but because we didn't have a lot of people it forced us to prioritize the critical, high impact things first.

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Having a small team can act like a barrier that blocks you from building a bloated product.

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I want to make more of a case for the above statement, but first I'd like to get a bit more into what we did during the 3 year period.

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Once we've build an initial version of the app and got our first customers we quickly realized that building a "second Gmail" is super-hard:

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  • Communication protocols (email/facebook/etc..) are complicated - we knew that before we even started, but it's difficult to describe the amount of work that needs to get done to make them work correctly. The amount of corner cases and weird protocol quirks is just staggering. In fact I would even go ahead and say that if you're integrating with any kind of external systems (webhooks, REST apis, etc..) then you're going to have a very hard time making them work correctly.
  • Having a highly-available and fast app is very hard when you don't have a team of full-time SREs. Scalability was not our big concern when we first started because we didn't have customers, but having an app that was always on was very important, remember the ~4h average session length? It meant that we had to make some architecture and infrastructure decisions that allowed for a high uptime.
  • Customer support software space has a very high barrier for entry these days. You need to have certain features before people start to even consider you as a platform. The switching costs are high as well because now you have to train your people on a new app and changing people's routine is hard.

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It takes a lot of effort to get to a point where you can compete with the likes of Gmail or Zendesk - both amazing products btw. This was definitely the case for us, for close to 2 years we had only a couple of customers and our product wasn't that good if we're being honest.

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So what changed a year ago? To put it simply: our product didn't suck anymore. Or sucked less. It had that minimum set of features and stability that made it attractive enough to our main customer base (Shopify merchants) that were passionate about productivity in the customer support space. That, and the tenacity of our CEO Romain who was convincing everyone that they should use us.

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So we started having our second wave of early adopters and all our hard work was finally starting to pay-off!

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Now that we had more and bigger customers we were starting to have performance issues, our app was slow, suddenly we were starting to get bombarded by viral facebook posts events or promotional events via an email campaigns, we didn't have enough monitoring in place, our app was pretty inefficient, the main database was a frequent source of congestion. So we started fixing those issues while still receiving numerous feature requests.

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Thankfully we didn't actually optimize our code that much before (no customers!) and there were a lot of low hanging fruits at first, but it still put a lot of stress on the team which was becoming tired and overworked and requested to hire more people to build those features and help with the performance issues.

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We all agreed that it would be for the best to have more people on the team, but hiring is hard. Competent coders are not just randomly looking for the next gig. SF is also a very expensive city and for a startup that raised $1.5M and a 2 years of money burned we couldn't really compete with other players in town. We've started working with some great devs in Europe, we worked with a few talented interns as well and we tried to get by until we could have more customers and hopefully raise some more money to hire more people.

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I could speak more about hiring in the Bay Area and there are a lot of things we did wrong and still have a lot of things to learn, but that's probably an even longer post than this one. But yeah, it's hard to find someone good, it's expensive, etc...

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So what is the situation right now? Well, it's not much better. We've raise d a seed extension round from SaaStr with Jason Lemkin and hired a few people in the Growth team, but we still have a hard time hiring in SF or remote. In the meantime we have a small team and want to talk about that.

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On the importance of saying NO

I think it's important to realize the advantages of having a smaller team and the single most important super-powers that you're forced to acquire is saying NO more often that you would with a bigger team. If you have a bigger team and say no to a feature, new platform, integration, etc.. it's harder to justify the decision. There are arguments like:

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... we have enough devs! They are paid to make features, so what's the problem!?

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... the data shows that 50% of our customers are saying that they want this or that feature, we must build it!

But do we absolutely need to build that feature? Are the customers going to be a lot less effective with your product otherwise? Is it going to be a big boost for them or just a nice improvement? Once a feature is there you have to maintain it, fix bugs, improve it, etc.. The thing with data driven decisions is that sometimes it can be biased towards some historical practice that might not have a place in your current world.

Now, I'm not saying that you shouldn't listen to your customers, you absolutely have to, but be sure you understand well what they want before taking action and understanding takes time. Having an artificial brake on your enthusiasm might be a good thing.

Engineers build things, the natural tendency is to accept any technical challenge because of ego, curiosity, fun, etc... It takes discipline to say no and stick by it. A small team is making it easier to do it.

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Automation

When you have a small team you're forced to automate a lot more often some of your workflows. You don't have the luxury to do repetitive stuff so:

  • You start writing more tests because you don't have people hired in QA and you don't want to repeat the same tests all the time.
  • You add optional static typing, linting and other code quality tools because you don't have time to deal with random type errors or have debates about tabs vs spaces.
  • You resolve repetitive bugs by doing some refactoring because you can't deal with the constant flow of tech support tickets.
  • You make a lot of tasks retry-able so if a HTTP request to facebook failed you don't have to manually retry them.
  • Cronjobs, cronjobs everywhere.

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Building the right culture is a long process

People that work at Gorgias come from different backgrounds and sometimes it can be challenging to be on the same page. In some cases our work processes are similar to many other companies:

  • Github for our code and issues.
  • Code-reviews on Reviewable - it's awesome!
  • Jenkins to build our docker images and upload them to google cloud.
  • Kubernetes to run everything on GKE.
  • Sentry to collect production errors.
  • Datadog to monitor everything.

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But there is so much more than just the above processes to engineering:

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  • The way we all come together and decide how certain things will be built or fixed.
  • The way we talk about a certain API decisions and refactoring.
  • The way we deal with an outage and a bad bug that affects our biggest customers.

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These things need time to happen to be embedded in your engineering consciousness and if you're the first-time founder (like myself) you also need the time to understand how to operate in this environment.

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Management overhead

Never managed a big team so I can't really speak about it's dynamics, but I would expect that because there are more people there is a lot more bandwidth you have to manage, a lot more people have to agree, a lot more politics have to be settled. I don't look forward to that to be honest, the more time I can get away with hiring as little as possible without a big sacrifice of our growth as a company the more I'll try to delay it.

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I conclusion I would say that it's totally fine to have a small team, in fact, I'm considering it a competitive advantage that you should try to keep as long as you can.

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The irony

I made a point in this post that having a small team is a competitive advantage, but I also think that we are ready to grow our team a bit. Yep, we're hiring!


No items found.
Octane AI Integration

Scale your Messenger marketing with Octane AI and Gorgias

By
1 min read.
0 min read . By

Facebook Messenger is becoming a new marketing channels for brands. They use it as a way to build personal relationships with customers and to drive higher conversion than traditional email marketing.

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Today, we're excited to announce our newest integration: Octane AI.

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The challenge with Messenger marketing

When a brand launches a marketing campaigns on Messenger, it typically leads to insane conversion rates. That's why the trend is on the rise.

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Another consequence is that a lot of customers respond to promotional Messenger communication. This generates a spike of support requests, that your support team has to deal with.

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Our integration with Octane AI lets you handle this support spike directly in Gorgias. Your agents have context about the customer: they see the conversation history before the Messenger conversation (did the customer email you last night?), and allow you to take action, like editing or refunding an order

What you can do with the integration

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  • Respond to requests from customers, to make sure none of them falls through the cracks
  • See the order data from Shopify next to your Messenger conversations
  • Automatically respond to common questions, such as "where is my order"

Customers are already using Octane AI and Gorgias. Here's what Live Love Polish has to say about the Octane AI and Gorgias integration:

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“We’re really thrilled that Gorgias and Octane AI came together to make the customer service experience over Messenger even better for our customers. Accessible customer service is central to what we do at Live Love Polish. Answering customer questions via Messenger has made our customers happier.”

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Do you want to give this a shot? If you use both tools, just connect your Facebook page to your Gorgias account and see the magic happen. If not, create a Gorgias account, or sign up for Octane AI.

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Do you have questions? Just hit the chat bubble, our team would love to tell you more about the integration!

No items found.
Integrate Your Smile Io Account To Gorgias

Integrate your Smile.io account to Gorgias!

By Axelle Heems
1 min read.
0 min read . By Axelle Heems

Loyalty programs are widely used amongst e-commerce merchants to grow and maintain market share by improving the number of repeat customers and attracting new ones. These programs come in different formats - from loyalty points to surprise gifts depending on the level of loyalty of each customer - and have proven efficient to help brands build a community of consumers based on the emotional attachment to their identity and values.

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As a customer support helpdesk, Gorgias is focused on providing the best experience for both end-consumers and support agents. Consequently, giving access to the most accurate information about your customers’ loyalty status enables your support team to adapt their answers to customer requests.

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Thus, it seemed only natural that we partner with Smile.io, a rewards platform that has helped over 20,000 merchants reward their most loyal customers for performing profitable actions.

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With Smile, you can create and manage reward programs such as loyalty points, referrals and VIP programs, to build a fruitful relationship with your customers.

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Because Gorgias is appreciated for its ease of use and automation tools, we have decided to build a strong integration with Smile: not only can your support team have easy access to all the necessary data about your customers, but they can also use Smile variables in canned responses (or “macros”) and automation rules.

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  • Display your customers’ Smile profiles next to tickets

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Display-Smile-profiles-next-to-tickets-1

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  • ‍Use Smile variables (loyalty status, points balance, VIP program, referral url) in both your macros and your rules
Use-Smile-variables

By integrating your Smile account to Gorgias, you’ll be able to improve yet again not only your customer support but also your customers’ engagement to your brand. Our early adopters of the integration are already thrilled by it!

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"We're loving the Smile integration so far! Having access to the variables in the automation features of Gorgias (macros and rules) is a game-changer, especially now that we're focusing on improving our loyalty program. It would be great if the integration went a little further in the future to enable editing loyalty points!"
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Chris Storey, Founder and CEO at Dinkydoo

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If you're already a Gorgias customer, you can connect Smile directly from your Gorgias account, in the Integrations section. If not, you can create an account here and get started in a few minutes.

Apps and Integrations
Announcing The Okendo Integration

Announcing the Okendo integration

By Axelle Heems
1 min read.
0 min read . By Axelle Heems

Here at Gorgias, our aim is to provide the best customer support tools to our clients, whatever their specific needs. The more you grow, the more we work to develop our offer so that you can benefit from a tailor-made spectrum of integrations. As your business becomes more successful, you need to adapt your website to a fast-growing community of consumers, especially regarding the quality of your reviews and how they appear.

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This is why today we are proud to announce our new partnership with Okendo, a customer-marketing platform perfectly suited for high-performance Shopify businesses.

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Okendo helps Shopify’s fastest growing companies like oVertone, Paul Evans and Dormify build vibrant customer communities through product ratings & reviews, customer photos/videos and Q&A.

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Along with this, Okendo gives you the tools to leverage customer generated content across other marketing channels such as Google Search, Google Shopping, Facebook and Instagram.

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Since one of the key advantages of using Gorgias is to manage all your customer support in one dashboard, we decided to design a straight-to-the-point integration:

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If a customer leaves low rating review such as < 3 stars and/or with negative sentiment, Okendo can automatically create a ticket in Gorgias. This way, your staff can quickly engage in a conversation with them to understand what went wrong, and address the issue immediately.

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Okendo-Review-screenshot-1

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We believe this integration will take your customer support teams to the next level, as Okendo has already convinced some of our key clients.

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"One of our biggest assets is our unique customer community, so being able to maintain it as active and engaged as possible is key for our business. And making sure that we address any negative experience efficiently and in no time is just as important: this is exactly what the Okendo integration within Gorgias has enabled us to do, by automatically creating a ticket for these cases with the review displayed right next to it."
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Dan Appelstein, Founder & CEO at BeGummy

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"Aside from being excellent at building shopper trust, reviews enable us to identify customers who, for whatever reason, have had a less than stellar experience. The Okendo + Gorgias integration enables us to flag these instances and automatically assign a Gorgias ticket to a member of our Client Services Team, so that we can follow up and do our best to assist them with whatever issues they're encountering. This integration, along with Okendo’s consistent availability and unwavering support, have made the integration between these two platforms seamless and successful!"
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Jae Sutherland, Director of Client Service at oVertone

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If you're already a Gorgias customer, we can introduce you to Okendo to implement the integration directly from your Okendo account. If not, you can create an account here and get started in a few minutes.

No items found.
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