An17 exhibitor insights_tuesday_the analytics playbook
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The Analytics Playbook of High-Growth Merchants
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An17 exhibitor insights_tuesday_the analytics playbook
- 1. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 The Analytics Playbook of High-Growth Merchants ROBERT MOORE, Head of Analytics, Magento Commerce SEAN FISHER, Director, eCommerce, Signature Hardware
- 2. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 The Analytics Playbook of High-Growth Merchants
- 3. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Robert J Moore Head of Magento Business Intelligence @robertjmoore
- 4. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Our Mission is to Inspire & Empower Data- Driven People Customers Include:
- 6. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 • Founded in 1999, • Online retailer of products for bath, kitchen and home • Based in Northern Kentucky ☆IR Top 500 (#222) ☆IR 50 Fastest Growing ☆IR Hot 100 2015 ☆2015 IR Excellence Award Redesign of the Year
- 7. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 The 3 Key Growth KPIs Acquisition Retention CLV
- 9. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Acquiring New Customers Monthly New Customers by Quartile By the end of year two, top performers acquire 5x more customers every month than their counterparts. 10 Q1 Q2 Q3 Q4 Months in Business 360 NewCustomersinThousands 8 6 4 2 0
- 10. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Expanding Your Customer Base Total New Customers by Quartile By the end of year three, top ecommerce companies have a customer base that is 2.5x larger than the next-best group. Q1 Q2 Q3 Q4 Months in Business 360 NewCustomersinThousands 25 50 75 125 150 175 200 225 100 0
- 11. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Signature Hardware Perspective New customer acquisition is still relevant for established retailers, just through a different lens. Sean Fisher Director of eCommerce
- 12. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Signature Hardware’s First 36 Months Total New Customers Longer wait for exponential growth in high consideration verticals.
- 13. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Signature Hardware’s Last 6 Years Total New Customers No longer exponential, but still growing.
- 15. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 It’s No Surprise: The Holidays Are Huge New Customer Acquisition Month 24% of customers are acquired during the holiday months. Jan NewCustomers 1.75 1.5 1.25 1 .75 .5 .25 0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 16. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 But Not All Dollars Are Spent Equally Repeat Spending Proportions, First 6 Months Rest of Year Black Friday Weekend Black Friday w/ Discounts 100% 80% 60% 40% 20% 0% $1.00 $0.81 $0.74
- 17. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 The Solution: Know What You’re Acquring Repeat Customer Rate Focus on acquisition channels that drive higher repeat rates. SOURCE 1 SOURCE 2 SOURCE 3 PercentofNewCustomersWhoPurchaseAgain Weeks Since First Order0 18
- 18. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Important Considerations Solution: Customer Segmentation • Acquisition Channel • Geography • Product Category • Promotions or Discounts • Customer Support Interactions Optimize for: • Repeat Purchase Rates • Customer Lifetime Value (CLV)
- 19. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 But How? Data Consolidation! Web/ Mobile Analytics Customer Support Shopping Cart Email Marketing Ad Platform Back Office
- 20. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Join Disparate Data Silos for Actionable Analytics • Email Address • Tickets Filed Orders • Email Address • Purchase Amount • Number of Orders Customer Support Database Transaction Database • Are customers more likely to come back if they interact with support? • Are customers from Facebook Ads worth more than Google Ads? • How often do customers who use coupons come back again?
- 21. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Signature Hardware Perspective Seasonality is worth studying even if your business does not have a peak season around the holidays. Sean Fisher Director of eCommerce
- 22. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Non Holiday Peak Seasonality New Customers – Q1 Leads the Way
- 23. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Non Holiday Peak Seasonality Repeat Spending Proportions
- 25. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Customer Retention is Difficult Percent of Customers Placing at Least N Orders in Their First Year 68% of customers will never purchase a second time. 1 2 3 4 5 6 0% 25% 50% 75% 100%
- 26. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Repeat Purchase Probability Repeat Purchase Probability During the Customer’s First Year 32% 53% 1.0 0.75 0.5 0.25 0 2 3 4 5 6 7 8 9 10 Number of Orders RepeatPurchaseProbability
- 27. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Revenue from Repeat Purchases Revenue From New & Repeat Purchases, Bottom Three QuartilesPercentofRevenue 0 New Repeat Months in Business 360 10 20 30 40 50 60 70 80 90 100
- 28. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Revenue from Repeat Purchases Revenue From New & Repeat Purchases, Top QuartilePercentofRevenue 0 New Repeat Months in Business 360 10 20 30 40 50 60 70 80 90
- 30. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Signature Hardware Perspective • Determining loyalty is difficult for low repeat businesses. • Loyalty has to go beyond repeat: customer satisfaction drives WOM. Sean Fisher Director of eCommerce
- 31. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Repeat Purchase Probability Repeat Purchase Probability During the Customer’s First Year 32% 53% 1.0 0.75 0.5 0.25 0 2 3 4 5 6 7 8 9 10 Number of Orders RepeatPurchaseProbability
- 32. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Repeat Purchase Probability Average During Customer’s First Year vs Signature Hardware Number of Orders RepeatPurchaseProbability 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 2 3 4 5 6 7 8 9 10 Ave Customer’s First Year Signature Hardware
- 33. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Repeat Purchase Probability Ave. Customer’s First Year vs Signature Hardware vs Signature Hardware AOV $900+ Number of Orders RepeatPurchaseProbability 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 2 3 4 5 6 7 8 9 10 Ave Customer’s First Year Signature Hardware Signature Hardware AOV 900+
- 34. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Customer Satisfaction vs Direct Traffic Revenue 4.4 4.5 4.6 4.7 4.8 4.9 5 $600,000.00 $700,000.00 $800,000.00 $900,000.00 $1,000,000.00 $1,100,000.00 $1,200,000.00 $1,300,000.00 Direct Revenue Customer Satisfaction Score
- 36. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Inputs: AOV and Repeat Purchases CLV-365, AOV-365, & ANO-365 by Revenue Quartile $0 $25 $50 $75 $100 0 1 2 3 4 AverageNumberofOrders Average Order Value Q1 Q2 Q3 Q4
- 37. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Your Top Customers CLV-365 Histogram 0 CustomerLifetimeValue 25 50 Percentile 75 100 $0 $1000 $2000 $3000
- 39. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Deep Segmentation: CLV Stores HIGHEST CLV HIGHEST CLV LOWEST CLV 20% 33% 67% 75% 20% 33% 67% Purchases Again $300 CLV Never Purchases Again $150 CLV Receives Subscription Order $300 CLV Unsubscribe $100 CLV Never Purchases Again $50 CLV Purchases Again $200 CLV New Customer Purchases $150 CLV 20% 60% Subscribes on First Order $250 CLV Purchases in Bulk on First Order $200 CLV Purchases Single Item on First Order $100 CLV
- 40. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Segmenting CLV Informs Smarter Actions • Know what “next action” drives the highest expected value for a given customer’s CLV • Understand the likely CLV of customers by channel based on their early behaviors • Spend your time and energy focusing on the most impactful customer populations
- 41. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 CLV - Signature Hardware Perspective • Aligning advertising toward the most accurate efficiency metrics • Lies, damn lies, and analytics • Finding propensity for repeat by initial cart value • Driving revenue through higher AOV Sean Fisher Director of eCommerce
- 42. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Raising AOV – Creative Merchandising
- 43. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Raising AOV – Continual Price Testing
- 44. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Recap Instrument your data for maximal customer insight Understand your customer segments and levers Keep your audience engaged and coming back for more
- 45. Retail’sBIGShow2017|#nrf17Retail’sBIGShow2017|#nrf17 Q&A Robert J Moore rmoore@magento.com @robertjmoore Sean Fisher Sean.Fisher@signaturehardware.com
Notes de l'éditeur
- RJMetrics CloudBI is an analytics platform for online businesses. Our platform connects to data sources you already use (Salesforce, MongoDB, Facebook Ads, Zendesk, etc.), and consolidates it into a central data warehouse where you analyze it using our chart-building interface. At RJMetrics we’re lucky to work with a broad range of ecommerce clients. We have clients all over the world, across a variety of categories, and at a range growth stages -- from startups making less than $1 million a year, to some of the fastest growing brands in the fortune 500. And they use RJMetrics to glean insights on their customers from data.
- Over nine months, Signature Hardware, an e-retailer of kitchen and bath products, transformed a text-based, database-centric website with more than 60,000 SKUS into a highly visual, modern shopping site with functionality that helps the consumer sort through the product customization opportunities available on the site. Built on the Magento Enterprise platform, Mark Morse, vice president of marketing, says the customization options—such as matching bathroom vanity tops with faucets and mirrors—has boosted the site’s vanity sales more than 250% and the site’s average order value has grown 14%. The site also is fully responsive to appeal to shoppers on all devices. Internet Retailer named Signature Hardware the winner of the Redesign of the Year Excellence Award for 2015.
- We analyzed data around the rate at which they are expanding their customer base, how they keep retention rates high amidst rapid acquisition, how they grow their group of loyal customers and why the keep a close on on customer lifetime value.
- For an ecommerce company, any given purchase will come from one of two customer types: new or repeat buyers. We see that by month two in business, top companies already break away from the pack when it comes to new customers, acquiring nearly 2x more new customers per month. This gap only widens over time.
- By the end of year three, top ecommerce companies have a customer base that is 2.5x larger than the next-best group. When a company’s acquisition rates are high, and their retention rates are stable (something we’ll discuss much more later on in the presentation), the size of your customer base expands exponentially.
- Avoid acquiring customers via heavy discounts and promotions
- Let’s start with building a customer base. What you’ll see in the data I’m about to show you, is that the accelerated growth of top performers is so much faster than other companies that we have to assume there is something else happening here other than just efficient acquisition and good retention. Smart acquisition and good retention practices will get you far, but first, you have to first have a great product and large customer base that wants it.
- Avoid acquiring customers via heavy discounts and promotions
- Avoid acquiring customers via heavy discounts and promotions
- Avoid acquiring customers via heavy discounts and promotions
- Nix?
- Avoid acquiring customers via heavy discounts and promotions
- By the end of year three, top ecommerce companies have a customer base that is 2.5x larger than the next-best group. When a company’s acquisition rates are high, and their retention rates are stable (something we’ll discuss much more later on in the presentation), the size of your customer base expands exponentially.
- Non-promotional strategy means times of high consumer intend can lead to higher repeat spending
- So there are 3 ways to increase CLV: increase your average number of orders per customer, increase the average order value, or decrease marketing spend.
- Before we go further, I just want to point out how hard retention really is. Only 32% of customers ever make a second purchase. Despite these statistics, top ecomm companies count on repeat purchases for a large percentage of their revenue.
- However, we saw in our Buyer Behavior Benchmark that repeat purchase probability increases with each order. In the average company, for example, there’s only a 32% chance that a customer who has made one purchase will make a second purchase, but there’s a 53% chance that a customer that has made two purchases will make a third. So getting a second purchase is difficult, but once a customer returns, it’s easier to get to that 3rd, 4th, and 5th order.
- In these two charts, we’re looking at the percentage of revenue from repeat purchases. The left shows the bottom three quartiles, and the chart on the right are your top performers. Already in month one, top ecommerce companies generate 20% of their revenue from return customers. And by the close of year three, they’ve experienced periods when they generate nearly 60% of their revenue from return customers. On the other hand, the bottom three quartiles show slightly different behavior. In month one, bottom quartile companies only see 13% of their revenue come from return customers. By the end of year three, they have yet to see that number go north of 55%. What’s important to remember here is that there is no “right” amount of revenue a company should be getting from return customers. If you’re getting 60% of your revenue from repeat purchases, you still need to maintain high acquisition rates. These charts can fool you; if a specific acquisition channel starts failing, the percentage from repeat purchases is going to go up, only because revenue from new purchases is going down. Top ecommerce companies are able to maintain balanced retention numbers while pouring thousands of new customers into the top of the funnel.
- In these two charts, we’re looking at the percentage of revenue from repeat purchases. The left shows the bottom three quartiles, and the chart on the right are your top performers. Already in month one, top ecommerce companies generate 20% of their revenue from return customers. And by the close of year three, they’ve experienced periods when they generate nearly 60% of their revenue from return customers. On the other hand, the bottom three quartiles show slightly different behavior. In month one, bottom quartile companies only see 13% of their revenue come from return customers. By the end of year three, they have yet to see that number go north of 55%. What’s important to remember here is that there is no “right” amount of revenue a company should be getting from return customers. If you’re getting 60% of your revenue from repeat purchases, you still need to maintain high acquisition rates. These charts can fool you; if a specific acquisition channel starts failing, the percentage from repeat purchases is going to go up, only because revenue from new purchases is going down. Top ecommerce companies are able to maintain balanced retention numbers while pouring thousands of new customers into the top of the funnel.
- So there are 3 ways to increase CLV: increase your average number of orders per customer, increase the average order value, or decrease marketing spend.
- Now 42% of order are repeats, steadily rising 5% every year for the last 4. Flat for the 4 years prior to that. Circumstantial evidence for WOM, revenue from direct traffic has been growing at a higher rate than our business as a whole and is well correlated with higher satisfaction rates.
- However, we saw in our Buyer Behavior Benchmark that repeat purchase probability increases with each order. In the average company, for example, there’s only a 32% chance that a customer who has made one purchase will make a second purchase, but there’s a 53% chance that a customer that has made two purchases will make a third. So getting a second purchase is difficult, but once a customer returns, it’s easier to get to that 3rd, 4th, and 5th order.
- However, we saw in our Buyer Behavior Benchmark that repeat purchase probability increases with each order. In the average company, for example, there’s only a 32% chance that a customer who has made one purchase will make a second purchase, but there’s a 53% chance that a customer that has made two purchases will make a third. So getting a second purchase is difficult, but once a customer returns, it’s easier to get to that 3rd, 4th, and 5th order.
- However, we saw in our Buyer Behavior Benchmark that repeat purchase probability increases with each order. In the average company, for example, there’s only a 32% chance that a customer who has made one purchase will make a second purchase, but there’s a 53% chance that a customer that has made two purchases will make a third. So getting a second purchase is difficult, but once a customer returns, it’s easier to get to that 3rd, 4th, and 5th order.
- CLV is kind of the ultimate KPI. It’s your average order value multiplied by the average number of orders. Then you subtract out your cost of acquiring customers. Once you start calculating and tracking this metric, things get much more interesting and you’re able to make the types of decisions that move the needle.
- Customer Lifetime Value was a huge theme of another benchmark RJMetrics released around buyer behavior. In that report, we found that top-performing companies have have a CLV that is 79% higher than that of their peers. This chart isn’t explicitly showing CLV, but it’s showing that top companies have higher AOV, and more purchases which result in a much higher overall CLV.
- And to bring into perspective just how important CLV is as a metrics to optimize your acquisition, check out this chart, which shows customer lifetime value broken down by percentile. After one year, the top 10 percent of customers on average are worth 6 times the industry average (a value of $154 we found in the same data set), while the top 1 percent are worth almost 18 times more. To put it in perspective, that means a single customer in the top percentile will spend more than the entire lower 50 percent combined. So what can you do with this information? The way to increase your overall CLV is by spending more on getting and retaining these super high value customers, and less on the customers that don’t come back and don’t spend as much. Doing research about the customers with the highest CLVs can give you some great insight into retargeting campaigns and how to craft your messaging and strategies around that buyer.
- CLV is kind of the ultimate KPI. It’s your average order value multiplied by the average number of orders. Then you subtract out your cost of acquiring customers. Once you start calculating and tracking this metric, things get much more interesting and you’re able to make the types of decisions that move the needle.
- Once you start measuring CLV across your other metrics, you start to uncover more actionable insights. For instance, this is my favorite chart from our new report. It shows that first purchase value is actually an indicator of how many orders a customer will place in their lifetime. When you bucket customers by the number of orders they place, then look at how their first order values compare to the average, we see definitively that loyal customers have higher first purchases. Repeat purchasers spend more on their first purchase than the average, and one-time purchasers are the only group that spends less than the average. With this information, you can increase your ROI, because you know which customers will come back again and again. Tailoring your marketing efforts towards those customers that spend the most on their first order is an example of pretty complex analysis to boost revenue down the line.
- Analytics are your friend, but easily misinterpreted. Different metrics are needed for different verticals and consumer purchasing behavior. Customer's first order is over $900, more than 2x as likely to purchase again.
- Raised price $100 without any impact on demand. Another $100 price increase tanked revenue.
- So just to recap, we’ve focused on three areas of a business: align data to customer insights, CLV, and retention.