Testing and analytics for the relationship age
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As email marketing matures, smart marketers are going to lengths to build testing into their plans. They’re measuring engagement and revenue, testing offers, cadence, targeting, and a great deal more.In this session, you will learn how to start building a plan that puts the customer back at the heart of marketing through testing, using insight and analytics. Kim Barlow, Senior Strategic consultant at Responsys and Jenna Buddin, Web Analyst at JD Williams will share the great story around how they have taken testing even further through segmentation, propensity scoring, and a website visitor scoring model. You will also hear how JD Williams build deeper relationships with their mobile audience and use testing to drive success around shopping cart abandonment.
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Testing and analytics for the relationship age
- 1. Testing and Analytics for the Relationship Era: Building Your plan & Generating Results that Matter Kim Barlow Senior Strategic Consultant – Responsys
- 2. Testing and analytics for the relationship era Building your plan & generating results that matter
- 3. Kim Barlow Jenna Buddin Senior Strategic Consultant Responsys EMEA Web Analyst JD Williams
- 4. Your customers are demanding a new kind of relationship.
- 5. Marketers who test well and consistently, earn up to 25% more than those who don’t!
- 6. 74% of those that regularly test report on having “excellent” or “good” ROI
- 8. Why the increase…..? Technology / platform limitations Knowledge Time & Resource
- 10. Your testing toolkit 3 important things before you can get started.
- 11. 1: Develop a flexible infrastructure 2: Identify the right platform 3: Understand your current performance
- 12. The 4 Principals 1: Think it. 2: Do it. 3: Review it. 4: Apply it!
- 13. 1. Think it.
- 14. Test for Success 1. Think it Set Objectives: Good objectives: Increase Revenue Increase Engagement Increase Customer Retention Objective writing tips: Great objectives: Increase Revenue Increase Engagement Increase Customer Retention from ‘x’ to ‘y’ in the next ‘z’ months Short and Simple Actionable Measurable
- 15. Test for Success 1. Think it What do you want to test to help you learn? Performance influencers
- 17. Clickthrough Rate Influencers social placement CTA’s acquisition source responsive design txt length navigation no. products Content video horizontal layout tone personalisation blog feeds engaged vs disengaged links vs buttons new vs returning Relevance customer vs prospect click category RFM
- 18. Never underestimate the CALL TO ACTION Visit Click here Book Bookmark Enjoy more Look Discover Take note More Pay attention Like Buy Join in Go Browse Share Download Shop See Start Explore Check it out
- 19. Conversion Rate Influencers include vs exclude Incentive duration of offer single product landing pages offer type custom offer time of day time category day of week
- 20. Test for Success 1. Think it Keep it simple Test 1 thing at a time Significance Avoid variables that might skew results
- 21. ROI / Ease Prioritisation Matrix D H Ease of Execution E Purchase Category Segmentation Personalised Recommendations Email Engagement Segmentation Return on Investment Browsed segmentation L Subject Line Pre-header Sub-Navigation Bar Day of Week Time of Day A/B copy Find a Store CTA
- 22. 2. Do it.
- 23. Test for Success 2. Do it! Document your Test Plan for easy reference
- 24. 3. Review it.
- 25. Test for Success 3. Review it… Use analytics to report on: • A/B split tests • Control groups • Variations • Channels • Audience segments Do this regularly!
- 26. 4. Apply it.
- 27. If this is you today… # delivered 475,000 # opened 66,500 # clicked 19,000 # orders 380 Revenue = £28,500 14% open rate 29% clickthrough rate 2% conversion rate £75 AOV
- 28. Take your reviewing and start testing # delivered 475,000 # opened 71,250 # clicked 20,663 # orders 413 Revenue = £30,994 15% open rate 29% clickthrough rate 2% conversion rate £75 AOV
- 29. ….add few simple tests # delivered 475,000 # opened 71,250 # clicked 23,750 # orders 475 Revenue = £35,625 15% open rate 33% clickthrough rate 2% conversion rate £75 AOV
- 30. ….and a splash of optimisation # delivered 475,000 # opened 71,250 # clicked 23,750 # orders 594 Revenue = £44,531 15% open rate 33% clickthrough rate 2.5% conversion rate £75 AOV
- 31. ….then, this could be you tomorrow # delivered 475,000 # opened 71,250 # clicked 23,750 # orders 594 Revenue = £48,984 15% open rate 33% clickthrough rate 2.5% conversion rate £83 AOV 72% Increase in Revenue
- 33. Jenna Buddin - Web Analyst
- 35. Key Challenges & Approaches • • • Using online and offline data together to influence a joined-up strategy 1. Segmentation Approach 2. Analysis by Device Evolving systems (and attitudes) to deal with multi-channel Demand capture and attribution 3. Advanced Program Testing
- 38. VIPs/Top Customers Return Rate of Each VE Rank Return Rate % 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Visitor Engagement Rank Propensity to Buy Score & Visitor Engagement Score
- 39. Marisota & Jacamo VIP sale emails vs. normal sale email results Demand per email sent up over 200% Vs. a control group: Response rate up over 100% Open rate up 17% Overall order rate was 3% higher Demand per account increased by 2%
- 40. Reducing Costs
- 42. The Usual Tests
- 43. Advanced Results (Post launch segmentation) Open Rate 30% 25% 20% 15% 10% 5% 0% Click Rate 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% Email 1 Email 2
- 44. Hold out groups Holdouts give us a great way of proving the value of our email programs
- 45. Abandoned Bag – Incremental Results Demand Per Account T C 1 T C 2 T C 3 T C 4 T C 5 T C T 6 C 7 2013 6% more likely to order spent 20% more 40% more likely to purchase abandoned product
- 46. Further Testing Potential: Introducing a Universal Control Group All new customers opting in No marketing emails 5% % 95% Any Emails
- 47. What’s next?
- 48. Targeted content
- 49. Testing email frequency by engagement segment 12mth lapsed when user joined inactive lapsing 6mth active 3mth passive 1mth Never 3mth last activity date new 12mth
- 50. Summary
- 51. Testing is a way of life! 1: Think it. 2: Do it. 3: Review it. 4: Apply it! And keep doing it!
Editor's Notes
- Are you willing to commit again?What does it look like to you?How could we get there
- However that being said it is also reported that today, fewer Marketers are testing and optimising when compared to 2008.
- All of these are great – but testing can start with just knowing some metrics
- Less than 5 seconds to make an impression: it’s the small things that count. Some of the smallest things matter the most
- Traditionally a mail order plus-size clothing company, now developed into a large multi-channel retailer.55% of sales now online, supported by email and social media.Brands cover a wide range of ages and sizes and include Simply Be, Jacamo, Marisota, Fifty Plus, Julipa. Recently opened 6 dual-fascia stores for Simply Be and Jacamo.
- Using online and offline data together to influence a joined-up strategyUsing online data for offline contact selection, reducing paper, modelling.Using traditional offline data for email selections, modelling and segmentation.Evolving systems (and attitudes) to deal with multi-channel Business Transformation project. Change management courses. Learning and presentations – particularly from our team – what can we offer from our web data?Demand capture and attributionWhich of the many channels led the customer to order? Celebrus data matching. Fair comparisons between channels. Email - last click.
- Selection Criteria:‘Overachievers’ – customers that have ‘beaten’ their Propensity to Buy ScoreHigh number of ordersHigh spendVisits:Orders Ratio low – so they checkout in the majority of their sessions (having had at least 2 sessions)High Visitor Engagement Rank
- The variables we include in these include both online and offline variables. Propensity to Buy Score: The likelihood and amount that we predict a customer will spend in the next 6 months. So 'overachievers' have spent more in the last 6 months than their score predicted 6m ago.Proportion of sales from front of catalogueNumber of incentives usedChanges to credit limitMost common order channelVisitor Engagement Score: The likelihood of a customer returning to one of our websites within the next month. Emails opened in last 3mDevices used to visit the siteNumber of departments purchased from (and which)
- Marisota and Jacamo VIP sale emails vs normal sale email:Open rate up 17% Response rate up over 100% Demand per email sent up over 200%We know these are better customers so we would expect their KPIs to be better, but it shows that emailing the right customers the right content works well. It’s worth emailing them – following a hold-out test for VIP emails we found:overall order rate was 3% higherdemand per account increased by 2%(in the 2 weeks following the email sent date)
- Both models used for the VIP segments use email stats as variables. We also take email statistics into consideration for our customer segments.We also use email to influence contact strategy decisions, for example our highly web-engaged emailable customers received a January Sale email and a postcard rather than a catalogue, enabling us to reduce costs. We tested this and saw no decrease in demand for the postcard group.
- Being able to see the customers’ sessions and to link back to customer data allows us to dig deeper into test results. The results may show one result overall, but it could be very different for certain customer segments.
- We have holdout groups for the majority of our email programs, e.g.Browse not boughtCross-sellAbandoned BagOne of our key difficulties is demand attribution. These holdouts give us a great way of proving the value of our email programs (and seeing if we've improved them or not!)
- For the 2013 abandoned bag test and control groups, in the 35 days after they abandoned their items:The group receiving an abandoned email were 2% more likely to order…And spent 6% more when they did
- Currently putting together method of testing a complete email holdout and a reduced email strategy.This will enable us to give a definitive value for the additional worth of emailing a customer.We also hope to gain insight into what frequency of emails is the right frequency. We can break this down into customer groups and by a customer's email engagement.
- In the coming months, we will be testing populating content dynamically based on a customer's preferences.For example, an email about dresses will have 3 types of content – holiday, smart and casual, and customers will see the content based on the type of products they usually buy or browse.Clearance email customers will see a clearance banner tailored to if they prefer dresses, tops or trousers. If they have never previously been interested in Clearance they won't receive an email at all – this will ensure we don't tempt customers into waiting for the products to reduce in price.
- Now we have governance in place, we can test the effectiveness of emailing customers with a strategy to suit their engagement segment e.g. active, inactive, lapsed.We will also look to implement our offline segmentation to give 1 joined up contact strategy with the offline contacts.