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Outperform Webinar Series: How to Optimize Your Checkout Flow & Engage Your Customers
The document outlines strategies for optimizing the checkout flow to enhance customer engagement and improve conversion rates. It emphasizes the importance of identifying key metrics, understanding customer problems, and implementing a structured experimentation methodology. Additionally, it discusses the significance of using both direct and indirect data to inform decision-making and hypotheses for testing.
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Outperform Webinar Series: How to Optimize Your Checkout Flow & Engage Your Customers
- 1. 1 How to OptimizeYour Checkout Flow and Engage Your Customers
- 2. 2 Housekeeping ● We arerecording this webinar ● You’ll receive the recording and slides ● We’ll answer all questions at the end
- 3. Alek contributes toOptimizely’s strategic practices on A/B testing and personalization. Since joining Optimizely, Alek has worked with the largest experimentation organizations to improve their program practices, up-level their methodologies, and build cultures of experimentation. Program Maturity and Scaling Led transitioned from a centralized model to a federated, Center of Excellence model. Improved team testing velocity by 10x in six months. Opticon Education Day Leader Led courses at both 2017, 2018, and 2019 Opticon on Full Stack Testing and Scaling Experimentation. Selected experience Alek Toumert Lead Strategy Consultant Education & Certification Miami University Bachelor of Arts, Business Legal Studies Areas of expertise & industry Lead Strategy Consultant, Optimizely Advise enterprise customers on best experimentation practices and scaling their program. Adjunct Professor, Digital Optimization, USF Leads course on best practices and industry trends in digital optimization in college of extended learning. Digital Analytics & Optimization Manager, American Medical Association Developed and led digital analytics and optimization program implementation and practices. Experimentation Methodology Instills best experimentation practices with teams to ensure strong hypotheses and analysis.
- 4. 4 Today’s objectives areto understand • which metrics to influence • using your data to find customer problems • how to structure strong hypotheses • review successful strategies
- 5. 5 The Experimentation Methodology Avoidinvesting in building experiences and features that won’t meet goals Minimize risk when releasing changes and new features Optimize for growth and maximize performance Plan & Ideate Iterate Analyze Prioritize & Design Build & QA Experiment
- 6. 6 Audiences Areas Metrics Goal Levers Experiments What are ourKPIs / business initiatives? How do we identify customer problems for those? Where and what is the problem? Who does it impact? What solutions could exist? Which is the best solution?
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- 8. 8 Audiences Areas Metrics Goal Levers Experiments What solutions couldexist? Which is the best solution? What are our KPIs / business initiatives? How do we identify customer problems for those? Where and what is the problem? Who does it impact?
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- 11. 11 Time Spent Listeningfor Music
- 12. 12 Time Spent Listening to Music Bringusers back more often Increase time spent per visit Output Metric Input Metrics
- 13. 13 Time Spent Listening to Music Bringusers back more often Increase time spent per visit Output Metric Input Metrics New Artist Notification Recommend ations Create Playlists Discover Weekly Views Input Metrics
- 14. 14 Revenue per Visitor Average Order Value Average Conversion Rate OutputMetric Input Metrics Average Quantity Average Per-Unit Price Add-to-Cart Rate Checkout Rate Input Metrics
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- 16. 16 Category Page Product Details Page CartPage Checkout Info Step 1 Checkout Info Step 2Purchase Path Primary Input Metric Output Metrics ● PDP page views ● Revenue ● Rates to completion ● Filter usage rate ● Scroll depth ● Search rate ● Bread crumb clicks ● Add-to-cart rate ● Checkout page views ● Checkout reviews ● Purchase conversion Purchase! ● Revenue ● Rates to completion ● Image click rate ● Attribute selection rate ● Scroll depth ● Recommendations clicks ● Revenue ● Rates to completion ● Navigation usage ● Scroll depth ● Search rate ● Bread crumb clicks ● Revenue ● Rates to completion ● Form field rates ● Time on page ● Search rate ● Navigation usage ● Revenue ● Form field rates ● Time on page ● Search rate ● Navigation usage Input Metrics
- 17. 17 What output metricsshould we focus on to improve our checkout flow? ● Revenue ● Purchase Conversion Rate ● Average Order Value ● Average Per-Unit Price ● Checkout Form Field Success Rates ● Add-to-cart Rate ● Promo Code Usage ● Average Time in Checkout Flow ● Loyalty Subscription Rate
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- 19. 19 Audiences Areas Metrics Goal Solution Possibilities Experiments What solutionscould exist? Which is the best solution? What are our KPIs / business initiatives? How do we identify customer problems for those? Where and what is the problem? Who does it impact?
- 20. 20 Using Direct andIndirect Data ● Web analytics ● Experiment results ● Voice of the customer ● Heatmaps ● User personas ● Usability tests ● Competitor sites ● Best-in-class experiences ● Blogs and webinars ● User groups ● Academic literature Data that you maintain to provide insights into your own business - this is Direct data. Many businesses use multiple frameworks and data source that help measure success and guide strategy. Data that you collect about the industry, your competitors, and external trends, these are Indirect data. This information is usually less structured or solved for by tools, and so needs to collected manually by motivated analysts.
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- 22. 22 Category Page Product Details Page CartPage Checkout Info Step 1 Checkout Info Step 2Purchase Path Purchase! 15% 60% 25% 85% 10% 5% 60% 39% 1% 40% 30% 30% 20% 50% 30% Continue down flow Exit siteRemains within site
- 23. 2323 This can beapplied to single page “flows.”
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- 25. 25 % of visitstaking next action Next step in funnel! 80% 15% Size Selection Add-to- Cart Color Selection 20%
- 26. 2626 Now that we’vefocused on “where”, we can focus on “what” the opportunity is.
- 27. 27 Isolate Pain Points ●What is distracting users from the primary action(s) we want them to take? ○ Do we want primary focus to be on our product images? ● Is attention correctly distributed to the points that would help user take that action? ○ Does clicking images first correlate to adding to cart? ● What is our user’s expectation from us at this point? ○ Are we providing a seamless experience from where the user arrived?
- 28. 28 What are ourtop entry channels? What are our top entry pages? What are our top exit pages?
- 29. 29 Which of theseactions correlates to conversion? “Re-searching” for additional products Interacting with the product images Interacting or clicking with related products Interacting or viewing product reviews Scroll depth to certain content blocks Interacting or viewing product info
- 30. 3030 We should alwaysconsider “who” as well when defining the problem.
- 31. 31 Category Affinity Product Affinity OfferAffinity Signed-In Abandoned Cart Device Browser Referral Source Time of Day New/Return KnownContextual Behavioral What do we already know?What is unique about them? What is their intent? NEW VISITORS RETURNING VISITORS KNOWN VISITORS Location Gender Purchase Frequency Past Purchases / Stores Payment Type
- 32. 32 Add-to-cart rate hasdropped by 5% over the last six months. Is this driven by a segment? ● Return visitors? ● Mobile visitors? ● Ad campaign visitors? ● Past purchasers?
- 33. 3333 Always keep inmind indirect data!
- 34. 34 Attributes not ina drop down Pictures listed, not in tabs
- 35. 35 WEB ANALYTICS HEATMAPPING USER TESTING COMPETITIVE REVIEW EXPERIMENT IDEAS
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- 37. 37 If I hadonly one hour to save the world, I would spend fifty-five minutes defining the problem, and only five minutes finding the solution.
- 38. 38 What qualifies agood customer problem? If you mention your product, service, or solution in the customer problem statement, then it’s probably not a customer problem. Customers want to be able to pay bills using their smartphone camera. All mobile banking customers want the convenience of easily paying bills on their mobile device but are required to enter payee details for every single transaction. We see a 45% drop off on the first form field entry and an average time on page that is 70% above site average.
- 39. 39 I need toget from A to B faster What is the cheapest and fastest way we can start learning? The skateboard is usable!
- 40. 40 Creating Solutions &Hypotheses
- 41. 41 Audiences Areas Metrics Goal Levers Experiments What solutions couldexist? Which is the best solution? What are our KPIs / business initiatives? How do we identify customer problems for those? Where and what is the problem? Who does it impact?
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- 43. 43 Add to Cart Rate Emphasizethe Primary Call to Action Wording / messaging Location / size Design / color / iconography Minimize Distractions Establish a visual hierarchy Remove non-critical content Limit number of choices Communicate Unique Selling Points Select/target the right USP’s Refine the messaging Communicate visually Recommendations Similar products Purchased with Goes Well Together Market Products Effectively Test ideal visuals (video, animation, text) Use the right review systems Find ideal description text / length Build a Sense of Urgency Show quantity left Push temporary offers Promote buying before set times Metric Strategies Tactics
- 44. Cart Checkout Rate Simplifying decision making Addressing questions / concerns Reducepressure of the decision Simplify consultation Seamless session continuation across visits Abandon basket e-mails Push last item viewed / redirect to conversion step Push the same product types Funnel path optimization Tailor user experience by selected funnel path (search v. browse v. deals) Reduce number of steps in finding and comparing products Redirect users to higher ROI funnel paths Reducing steps in checkout Skipping upsells Reduce questions / steps Pre-fill data Personalize throughout the flow Targeted offers / content displayed Messaging + Unique Selling Points adjusted by user segment Marketing + Imagery per audience Seasonality Product selection by season Tailor to varying user intent (purchase versus research) Optimize landing pages per season Metric Strategies Tactics
- 45. 45 Problem (w/ goal) Solution (w/ rationale) Measurable Hypothesis Ifwe highlight attribute selection prior to add-to-cart click attempts, then we will improve our 5% reduction in add-to-cart rate, because it will make it clear the steps needed to be able to order in advance. “If (solution) solves (problem), then (goal) because (rationale).”
- 46. 46 What should Ifocus on?
- 47. 47 What output metricsshould we focus on to improve our checkout flow? ● Revenue ● Purchase Conversion Rate ● Average Order Value ● Average Per-Unit Price ● Checkout Form Field Success Rates ● Add-to-cart Rate ● Promo Code Usage ● Average Time in Checkout Flow ● Loyalty Subscription Rate
- 48. 48 Focus on... ● Metricsfirst! Identify what are the metrics that are priority to influence in your checkout flow and outline those clearly for your team. ○ Understand how page specific metrics correlate. ● The problem statement is most important. Use multiple data sources (two!) to create a strong problem statements for the team to ideate on. ● Fill your backlog with all possible solutions! You never know what will move the needle. ○ There should be opportunity for multivariate testing for a new problem. ● Set a learning plan upfront so action and iteration is clear after your experiments.
- 49. 49 How to OptimizeYour Checkout Flow and Engage Your Customers