Forrester & SDL - Optimizing eCommerce Experiences

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Sucharita Mulpuru of Forrester shares online retail research and best practices for eCommerce marketers to optimize and personalize the customer experience. Tom Smith, SDL, talked through the 6 key elements of experience-Commerce with examples from ASOS, Majestic Wines and many others.

Transcript of Forrester & SDL - Optimizing eCommerce Experiences

  • 1. SDL Proprietary and Confidential Turning Browsers into Buyers: How To Optimize the eCommerce Experience Sucharita Mulpuru, VP and Principal Analyst, Forrester Tom Smith, Product Marketing Manager, SDL March 19, 2014

2. From brand experience, to customer experience A brand is more than just your logo 3. Customer Experience = Brand & Commerce in Harmony Your customers have one view of you, dont give them reason to change that perspective 4. Likes HP 52 years old Bought a tablet month ago Looking for a sports car Shopping for golden ear rings On the street using 3G, no wifi access points Location: New York The Rise of Context Tying the scattered, digital existence to the actual, physical self Early evening Using an Android 5.7 inch device Travels KLM 5. Shoppers dont think online vs. offline Being relevant, is more relevant than ever 6. Old school merchants and marketers limit their focus to the transaction 7. The Millennial Generation demands more experience Commerce 8. 2013 Forrester Research, Inc. Reproduction Prohibited 8 Three drivers of web shopping Top 2 box of 1-5 scale CONVENIENCE SELECTION VALUE Source: Forrester Benchmark Recontact Survey 2013 63% 68% 70% I find better values and deals online I save time by shopping online I find products online that I cannot find anywhere else Base: 4,476 online adulsts 9. 2012 Forrester Research, Inc. Reproduction Prohibited Most sales will continue to happen in stores 10. 2012 Forrester Research, Inc. Reproduction Prohibited The number of smartphone and tablet users are growing rapidly 11. Site metrics continue to be challenged 2.2% 2.9% 0% 2% 4% 6% 8% 10% 2000 2010 Conversion Rates 53% 55% 0% 20% 40% 60% 2000 2010 Cart Abandonment Rates $3 $3 $0 $1 $2 $3 $4 2000 2010 Customer service $/order 40% 35% 0% 10% 20% 30% 40% 50% 2000 2010 Repeat Shopper Revenue Source: Forrester and State of Retailing Online Studies 12. Phase 1 (1990s-2001) Phase 2 (2001-2008) Phase 3 (present) Site optimization efforts have evolved Site launches Licensed solutions Limited budgets Functionality constrained by bandwidth Functionality enhancements from point solutions Plug-in modules One-for-all execution Basic site improvements Dynamic optimization Integration of broad datapoints One-to-one execution Mainstreaming of cloud infrastructure 13. Phase 2 introduced many now industry standard features 14. 2013 Forrester Research, Inc. Reproduction Prohibited 14 Agenda Optimizing the experience Examples 15. Interactive marketing helped to evolve eCommerce executives to dynamic thinking Testing of copy and creative Dynamic adjustment of datafeeds Personalized content and segmentation based on previous clickstream history Landing page optimization 16. Turn browsers into buyers by using Intent from on-site search, or search engines Current interests from clickstream Recommendations which can be adjusted to a shoppers visit Items in cart as a trigger for cross-sells and upsells Insight on whether the visitor is a repeat or first-time visitor Location of the customer (direct or inferred) Dynamic pricing Browser type and mobile information to adjust content 17. Some retailers have been doing this for over a decade 18. Smarter store windows can be incorporated throughout the site experience Site touchpoint Opportunity Homepage/landing page Promotional offers to various customer segments Smart shipping; vary offers based on the most cost-effective shipping option Content variance based on geography of viewer Sort site search by inventory availability Product detail pages Personalized recommendations Live support for shoppers based on inferences about likelihood to buy Changes in pricing or offers based on browser and location (e.g. in-stores and mobile search) Offers based on consumer likelihood to buy Checkout Personalized recommendations and offers Same session offers 19. 2013 Forrester Research, Inc. Reproduction Prohibited 19 Agenda Optimizing the experience Examples 20. Do incorporate recommendations throughout the shopping experience 1 2 21. 3 4 22. Recommendations during search results expose useful products at key moments 23. Do put recommendations in email Order Confirmation Shipping Confirmation 24. Do put recommendations above the fold where possible 25. Product detail pages should upsell while checkout cross-sells best 26. Do think about the verbiage for describing your recommendations 27. Faceted navigation is now table stakes 28. Different treatments for different visitors First time visitors get a special offer 29. Do consider suggestive search 30. Do constantly tweak your algorithms 31. 2013 Forrester Research, Inc. Reproduction Prohibited 31 Adjust what is rendered according to the device 32. A few donts to think about Dont neglect your product recommendations feature, even if you plan to set and forget Dont expect recommendations to overcome clumsy taxonomy Dont underestimate the challenges of doing this in-house Dont ignore your companys unique challenges in the due diligence process 33. 2013 Forrester Research, Inc. Reproduction Prohibited 33 A superior customer experience = a stronger company overall 34. Thank you Sucharita Mulpuru [email protected] 35. The eCommerce Experience Challenge 35 How do I build a differentiated, forward- thinking digital shopping experience while everything changes around me, day to day? How do I invest in top priority projects while thinking about the customer experience is mobile more important than video, than international, than merchandising, than omnichannel? 36. The eCommerce Experience Challenge 36 How do I stop working on a hunch and more on the data I know will tell me more about how to optimize for my customers? How do I bring all the eCommerce experiences together into one holistic experience that aligns with KPI goals AND brand goals? 37. Towards Experience-Commerce 37 From: Transaction Focus To: Experience Focus Basic Catalog Content Exposed Minimal data points, little understanding of customer context Division between channels Pushing products Silos between content/brand & eCommerce teams Minimal international understanding 1. Catalog Enrichment 2. Context-awareness and Data- influenced Experiences 3. Satisfying the Omnichannel norm 4. Influencing Product Discovery 5. Blending Content + Commerce 6. Refined, controlled international eCommerce 38. 1. Catalog Enrichment * Invodo research 2013 How Consumers Shop with Video: Video + interactive imagery = Engaging the Customer & Driving to Purchase 55% of consumers are more likely to purchase after watching a video* 39. Likes HP 52 years old Bought a tablet month ago Looking for a sports car Shopping for golden ear rings On the street using 3G, no wifi access points Location: New York The Rise of Context Its about the mobile consumer, not the device Understand time, device, location and profile Derive insights from behaviors Guide the experience Early evening Using an Android 5.7 inch device Travels Delta 2. Context Awareness 40. 2. Data-driven Merchandising 40 Moving an item by one row equals a discount of up to 6% for a short product list and medium position dependent products* Moving an item by one row equals a discount of up to 21% for a medium-length product list and highly position-dependent products = Moving products has a similar effect as a discount *Based on an experiment with hypothetical purchase decisions. 9 or 27 options per decision. Medium position dependent product: suitcases, highly position dependent product: wine. 41. 3. Satisfy the Omnichannel Norm 41 Unified Experience Flexibility and seamless shopping Full product offering across all channels Single view for the customer across all channels Single organization servicing all channels Omnichannel Retailer Some cross channel capabilities Single brand access across all channels Separate supply chains and systems Cross-channel Retailer Different channels in silos Silod business units Stock availability High level customer service Product variety Differentiated services Multi-Channel Retailer Bulk of revenue from one channel Traditional brick and mortar retailer Pure play online retailer Single Channel Retailer 42. 3. Satisfy the Omnichannel Norm 43. 4. Influence Product Discovery 43 One of the problems with e- commerce today is the tendency to equate search with shopping. Shopping is not a utilitarian function, but instead, a process of discovery. Think of a time you visited a store and found something wonderful, something unexpected. You dont have to give that up in order to shop online. ~ Hiroshi Mikitani, CEO, Rakuten ~ 44. 5. Blending (Relevant) Content + Commerce 44 45. 5. Blending (Relevant) Content + Commerce 45 46. 5. Blending (Relevant) Content + Commerce 46 47. 6. Internationalization Centralized merchandising control? Or local flexibility? Language considerations? Propensity to shop on smartphones, tablets? Prefer video & imagery? Less likely to make a purchase without going in-store? 48. 7. Internationalization 48 Sneakershoetrainerrunning shoe? 49. SDL for eCommerce: Optimize & Personalize Optimize conversion rates 18-40% Make shopping inspiring, intuitive and part of the complete customer experience Give your merchants and marketers control over the digital shopping experience Blend multiple data sources to personalize for each and every customer, regardless of channel eCommerce 50. SDL for eCommerce Optimization and Personalization Data-driven Merchandising Predictive Targeting Business Management Layer Predictive Analysis & Optimization Data Manager Personalization Search & Navigation Brand or Shop Branded Store Experience 51. Global Retailers We Work With 51 52. SDL Custo