Benchmarking Ecommerce KPIs

Let's talk about e-commerce KPIs that are important, but you may not be tracking. These are great leading indicators to spot if something is amiss and can help you run a more profitable and effective business. 1) Days Between Purchases What is the average number of days between the first and second purchase? In most cases, we are aiming to reduce this over time as customers become much more sticky if they can purchase 2+ times in their lifetimes. A tactical way to close the gap is your post purchase email flows - are you taking advantage of cross-sell/upsell opportunities in high open rate emails such as order and shipment confirmation emails? 2) % of Product Page Views What percentage of your traffic makes it way over to the product pages? We keep an eye on this as a trend in order to see if the quality of our traffic is up to snuff and if the site is developing any unwanted friction between upper level pages vs. pages deeper in the funnel. 3) Add to Cart % & Checkout Passthrough % The cart/checkout experience is one of the most valuable and high impact places on your site. We have often reversed sudden dips in this due to malfunctioning coupon codes, technical issues, pricing presentation issues, etc. and this has saved us and our clients a lot of money! 4) Revenue by New & Returning Customers We analyze trends in this over time to ensure our media mix is achieving its goals and also to see if we have any issues with retaining our customers. We were surprised in the past to see things like slow shipping times heavily affect returning customer revenue over long periods of time. 5) E-Commerce Search % For certain sites/brands, we see great conversion rates (up to 5x higher than average) whenever someone uses the search function on their sites. We aim to slowly increase search usage or experience over time in order to get customers closer to where they need to go. Amazon thinks that this is so critical that the search bar dominates every page on their site. 6) Site load times Site load times are critical to the customer experience and to conversion rates, but are often ignored and not tracked over long periods of time. A key piece of managing this is ensuring third party pixels are behaving well and are not unnecessarily kept on the site as your needs fluctuate and change. 7) Customer NPS / Customer Service Metrics (avg. time to fulfill order, etc) These metrics positively correlate to repeat revenue and order %. It's also a great way to "talk" to your customers since these surveys can be incredibly revealing and surface issues that are holding your business back, such as issues with products being damaged during the shipping process. KnoCommerce is a great tool to execute this! Lastly, we use an extremely customized dashboard from Databox to track and monitor all of these KPIs while being able to see weekly, monthly or quarterly trends. Any other lesser known metrics that are worthy of tracking?

A $50M+ ecom client recently asked me what a "great data setup" looks like. My response: It depends. But, for these guys (omni-channel, multiple countries, high price point)... Data Collection & Storage - clean and accurate data layer - server-side tracking for all major platforms - critical conversions and engagements tracked (web/app/offline) Governance - standardized naming conventions (metrics, UTMs, campaigns) - accurate data relative to source systems (oms, erp) - centralized user opt-in Measurement - attribution modeling (in-channel) - testing culture across all channels - incrementality and experiment-led measurement (holdouts, MMT, MMM) - qualitative and csat data collected and funneled back to business (merchants, ops) Customer & First-Party Data - single customer record across systems (online/offline, loyalty, cs) - customer data secure and governed - id resolution (cdp/cdp-lite/identity-graph) - Customer-level metrics drive business (LTV, CAC) - centralized audiences and segments Data Storage & Enablement - all data stored in same place (eg. cloud warehouse) - automated data pipelines to blend and clean data - up-to-date data dictionaries and schemas BI/reporting - data available when you need it (daily, weekly, real-time) - specific data by team (exec, departments, analysts) - ad-hoc/query access for data teams - no unnecessary reports - warehouse and pipelines optimized for cost and performance Trust & Team - your team trusts the data without hesitation - your team uses the data (forecasting, planning, optimization) - your team understands the data - KPIs mapped to owners (teams) Not all of this applies to every business, especially smaller ones. What else would you add to this list? #ecommerceanalytics #measure #dataanalytics

Let's consider a real-world example of how connecting KPIs can lead to valuable insights and informed decision-making: Imagine you're managing an e-commerce business, and you're keen to boost sales. You have several KPIs, including: 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐑𝐚𝐭𝐞 (𝐂𝐑): The percentage of website visitors who make a purchase. 𝐀𝐯𝐞𝐫𝐚𝐠𝐞 𝐎𝐫𝐝𝐞𝐫 𝐕𝐚𝐥𝐮𝐞 (𝐀𝐎𝐕): The average amount spent by a customer in a single order. 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐀𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐂𝐨𝐬𝐭 (𝐂𝐀𝐂): The cost of acquiring a new customer. 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐋𝐢𝐟𝐞𝐭𝐢𝐦𝐞 𝐕𝐚𝐥𝐮𝐞 (𝐂𝐋𝐕): The predicted revenue a customer will generate during their relationship with your business. Here's how you might relate these KPIs: 𝐂𝐨𝐫𝐫𝐞𝐥𝐚𝐭𝐢𝐨𝐧 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: You notice a positive correlation between CR and AOV. As the average order value increases, the conversion rate also goes up. This suggests that strategies aimed at increasing AOV, like offering bundled products or discounts for higher cart values, could lead to improved conversion rates. 𝐂𝐨𝐡𝐨𝐫𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: You group customers by their acquisition channel and analyze their behavior over time. You find that customers acquired through social media have a higher CLV compared to those acquired through paid search. This insight allows you to allocate more resources to social media marketing. 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤𝐢𝐧𝐠: You compare your AOV to competitors in the same niche. If your AOV is significantly lower, it might indicate an opportunity to increase prices or implement cross-selling and upselling strategies. 𝐂𝐚𝐮𝐬𝐞-𝐚𝐧𝐝-𝐄𝐟𝐟𝐞𝐜𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: You discover that a spike in CAC is associated with a drop in CLV. Upon investigation, you realize that a recent advertising campaign increased acquisition costs without proportionally increasing customer value. You decide to optimize your marketing strategy to maintain a healthy balance. 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: You create scenarios to test the impact of different strategies on your KPIs. For instance, you simulate the results of offering free shipping for orders above a certain value. This could lead to higher AOV and potentially increased CR, but it will also affect CAC and, in turn, CLV. By connecting these KPIs and analyzing their relationships, you gain a comprehensive view of your e-commerce performance. This empowers you to make data-driven decisions to optimize your sales strategy, allocate resources effectively, and ultimately grow your business. Remember, the key is not just to collect KPIs but to understand how they influence one another and how you can leverage this knowledge to drive business success

One of the biggest mistakes I see is treating metrics as KPIs when they’re really just numbers with no context. If you can’t compare a metric to something meaningful, it’s not a Key Performance Indicator—it’s just noise. 🚫 “Our conversion rate is 2.3%.” 🚫 “Our average order value is $85.” Ok… but compared to what? 🤷♂️ KPIs only work if they measure against: ✅ Historical performance – Are we improving over time? ✅ Industry benchmarks – How do we stack up against competitors? ✅ Goals & expectations – Are we meeting or exceeding targets? If you’re struggling to set KPIs, here are three practical ways to establish meaningful comparisons: 1️⃣ Back of Napkin Estimate (The Quick & Dirty Approach) 📌 What It Is: Using past data, experience, and intuition to create a reasonable target. 📌 How to Do It: 🔹 Look at historical performance for the same time last year/month. 🔹 Factor in external influences (seasonality, trends, promotions). 🔹 Use industry benchmarks if available. 📌 Why It Works: It’s fast, and even a rough target is better than no target at all. Example: A retail eCommerce store sees that last year’s Black Friday conversion rate was 4.2%. Given new promotions and increased ad spend, a reasonable KPI might be 4.5%-5%. 2️⃣ Bracketing (The Logical Process of Elimination) 📌 What It Is: Working with your team to determine what’s way too low, what’s way too high, and narrowing in. 📌 How to Do It: 🔹 Ask: “What’s an unacceptably low number?” → This is your floor. 🔹 Ask: “What’s a ridiculously high number?” → This is your ceiling. 🔹 Keep refining until you land on a reasonable target KPI and a stretch goal. 📌 Why It Works: Helps teams align on realistic vs. aspirational goals. Example: A startup wants to set a KPI for customer acquisition cost (CAC). 🚫 $5 CAC is unrealistic—it’s way too low for their industry. 🚫 $500 CAC is unsustainable—it would kill profitability. ✅ Through discussion, the team brackets down to a realistic $80 target CAC, with $60 as a stretch goal. 3️⃣ Pick a Number & Adjust Later (When No Data Exists) 📌 What It Is: When you have zero historical data or benchmarks, just pick a number and adjust later. 📌 How to Do It: 🔹 Choose a starting KPI that seems reasonable. 🔹 Track performance for a few weeks/months. 🔹 Adjust the KPI based on real-world data. 📌 Why It Works: A bad KPI is still better than no KPI. You can refine over time. Example: A brand-new DTC skincare brand is launching its first paid ads. No data, no benchmarks. 🔹 They set an initial target of a 2% conversion rate based on general eCommerce benchmarks. 🔹 After 3 months, data shows they’re consistently at 2.8%—so they adjust their KPI to 3% as a stretch goal. Final Thought Too many businesses treat metrics as KPIs, expecting them to magically drive decisions. But a KPI without comparison and context is just a number. How do you set KPIs in your business? Drop your approach below! 👇 #Data #KPI #BusinessMetrics #Analytics #DecisionMaking

Ecommerce data is messy. Sales spike, traffic dips, and ad campaigns come and go So how do you find a reliable baseline? If you just look at the last 30 days and call it your baseline, you’re flying blind. Ecommerce performance is constantly shifting, and short-term data is full of noise. We start by zooming out looking at a rolling 90-day window. Go deeper than global metrics. Understand all the highs + the lows. Account for wild swings and anomalies. This helps us spot patterns, smooth out volatility, and capture a more comprehensive view. But even that’s not enough unless you layer in context: - Were there inventory issues? - Did the brand run a promotion? - Was there a product launch? - Did paid ads spend and strategy shift? Without these details, your data is just numbers on a screen. They can paint a pretty little chart or fill up a table,  but beyond that what can they really tell you? And even when the surface looks stable, unexpected swings still happen. We’ve seen intra-site funnel metrics jump 5-15%  from one month to the next many times with no rhyme or reason. Seasonality or even broader market shifts can throw things off in ways you can’t predict. The truth is, no baseline is ever “perfect.” The goal isn’t precision → it’s perspective. Zoom out to identify long-term trends, then zoom in to set a working benchmark. It’s not a rigid target → it’s a living metric that evolves as the business grows. It’s a way to hold yourself accountable and to measure your efforts. Without it them how will you know how you’re performing? Because without clear data-driven baselines, you’ll miss the massive shifts. Whether good or bad. You’ll never know they happened. And you’ll definitely never understand why.

Part 2: Getting to your first $1mm on Shopify. After growing to $100k you should now have data you can use to improve your business. KPI’s to optimize are: - conversion rate - average order value - repeat purchase rate - CPA - ROAS - email opt-in rate Here’s how: 1. Increase your Average Order Value (AOV) The math is pretty simple. Get customers to add more value to their cart, and your revenue goes up. So how can you do it? - Bundle frequently purchased products together.  - Create multi-unit packs to offer more value eg. a 3 pack for 15% off.  - Cross-sell to more expensive products. You can do this on PDP’s, homepage, or triggered by an add-to-cart or post-purchase. Bold Commerce and Zipify are apps that can make this easy 2. Optimize your email flows Optimize your subject lines and you’ll boost open rates. Set up A/B tests for these if you haven’t already. Add content answering objections and frequently asked questions to the welcome series. Add the social proof you now have: testimonials, review ratings and pics. 3. Boost your repeat purchase rate Getting your customers to purchase time and time again means you’ll continue to earn revenue after spending money to acquire them. This is huge for e-commerce, especially as CAC’s have been rising. How can you do this? - Enable and customize a loyalty program - Offer subscriptions  - Email campaigns You can also run special promotions to previous customers via paid ads to give them another reason to come back. 4. Reduce your CAC / CPA To get to $1mm in sales, you’re going to need to test and scale new assets. Test new hooks, angles, offers and creative types. Test algorithmic campaigns ie Pmax on Google and Advantage+ on Meta. Highlight social proof that features key benefits and pain points. Motivate referrals via a loyalty program and reinforce with email and product inserts. Cut copy and creative that under-performed. And push budget toward winners and new creative so you can feed the Meta machine. Bonus points: test new content organically and then scale up the assets that out-performed via paid ads. 5. Increase conversion rate On your path to $1mm you’ll want to do CRO “light”. This means going with best practice. There’s tons of low hanging fruit you can capture: - Lead with best-sellers now that you know what customers are buying - Add social proof everywhere - Add copy from customers - Consider a chat widget - Cut all unnecessary distractions on the path to purchase - Optimize your welcome pop opt-in offer Sound like a lot? It is. And optimization never stops. But if you get 1% better every day, in a year your business will be transformed. And that’s what it takes to get to your first $1mm (and beyond) on Shopify. What did I miss? ------------------- Follow for tips on growth marketing for early-stage Shopify businesses. #shopify #dtc #ecommerce #marketing #digitalmarketing