practical ways to use dynamic recommendations

pg. 2

IntroductionThe objective of marketing strategies that use technology to present dynamic recommendations is simple– to get the customer or prospective customer to take the next action… by suggesting what that “action” should be. For the customer, it answers a valuable question: “Based on who you are, what should you do next?” In a world of fragmented and hyper communications, those that are highly relevant and which make suggestions that are easy to act on are very valuable to customers…and very productive for marketers. While all recommendations don’t necessarily have to be about what to purchase, these are cases that many are familiar with (and it’s easy to extend these into non-retail purchase situations):

“Next steps” You bought a shirt; next, you may want to purchase a tie that compliments it

“Similar product” You bought a shirt; you may be interested in other similar shirts

“Best sellers” You bought a shirt; the best-selling items in our store right now are these belts

“Something new” You bought a shirt; you may be interested to know that we have some new products that you haven’t seen

“People who bought, also bought” You bought a particular type of shirt; other people who bought that also bought this particular wallet

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1.877.937.6245 | [email protected] | www.yeslifecyclemarketing.com pg. 3

This whitepaper: • Describes why providing recommendations through dynamic content is worth pursuing

• Defineswhatdynamiccontentis

• Offersaframeworkforhowtothinkaboutapplication of the concept

• Discusses options for how to use the framework

• Makes practical suggestions for how to implement and apply

About Yes Lifecycle Marketing: Yes Lifecycle Marketing is a solution provider that brings together multichannel marketing platforms and data, with creative and strategy services honed on the optimization of delivering relevant marketing messages. This gives marketers the ability to source best-of-breed technology and creative and strategy services from asinglevendoratacost-effectivepricepoint.Formoreinformation,visitwww.yeslifecyclemarketing.com.

pg. 4

Why Should You Implement Dynamic Recommendations?Marketersrealizethatprovidingdynamicrecommendationstakeseffort…soitbetterbe valuable. There are several key arguments for why you should consider providing recommendations: • Automating the merchandising function increases the situational relevance for customers.

This encourages incremental and repeat purchases; it also improves perception of brands that demonstrate they understand and value service. It is particularly important in very competitive industries and with companies that have large numbers of products and stock-keeping-units (SKUs). It can help buyers who increasingly face a choice overload problem, and research has shown that buyers with reduced choice in some cases may be 6x more likely to purchase (see Sheena Iyengar’s Ted Salon presentation, “How to Make Choosing Easier”, https://www.ted.com/talks/sheena_iyengar_choosing_what_to_choose).

• It’s proven. Amazon made headlines doing it over a decade ago. Since then, automation has been developed that makes the concept available to most merchants. Vendors like Baynote andIBMclaimclientbenefitsof40-50%greaterengagementand10-12%increaseinsales.

• It’s a mature concept. Customers accept it and more and more expect it. It makes their shopping and decision-making easier. This is increasingly important with the increased use of mobile devices.

There’s plenty to read about the techniques and technology that enable dynamic recommendations.*Sufficeittosay,thatalotoftime,money,andresourceshavebeenappliedto develop, gather, store, analyze, manage, and use relevant data. It requires steps to determine user and item similarity, classifying, and the “recommenders” that make the decisions. The titansof“tech”,likeNetflix,LinkedIn,andtheaforementionedAmazonhavebeenleadersin developing and using these approaches. Their successes have led to the creation of the development of many commercially available solutions. These solutions contain skillful models that outperform simpler alternatives…even if those alternatives could scale (which most often they cannot).

*They include the Apache Mahout framework for collaborative filtering, clustering and classification.

https://www.ted.com/talks/sheena_iyengar_choosing_what_to_choose


Factors to Consider When Implementing Dynamic RecommendationsThere’s a lot of data that should be considered when determining what to recommend for aparticularcustomer.Thisincludesdatawheremanydifferentperspectivesneedtobeconsidered:

Additional factors may include: • Whether the seller has a longer-term objective, for example to re-activate a customer who

has not purchased in some time

• How an individual behaved on a seller’s site in the past

• How to use contextual data compared to historical (e.g., “CRM data”)? For instance, we may know a woman shopper has a history of buying certain women’s products but, during a particular session, she is looking at products for men. At the same time, we may have results from a predictive model that indicate that the same woman is more likely than other women with similar characteristics to buy boating products.

• What is known about a customer’s expressed preferences is also important. Many companies encourage customers to indicate products, brands, and or categories that they are most interested in.

Some recommendationions that a marketer may take range from relatively simple to complex, based on the item’s characteristics as well as the characteristics of the individual. Examples of the characteristics that vary from simple to more complex include:

• ”Global” rules that could be applied to provide recommendations for men vs. women, by age group, or by geography, e.g., beach vs. mountain living

• Lifestyle, e.g., “active lifestyle” vs. more reserved

• Atanindividuallevel,itcangetimmenselyspecific,butforasportinggoodsretaileritcould just include consideration of the types of sports that an individual prefers, e.g., basketball vs. lacrosse

What’s easy to get started with?

• Gender

• Age

• Location

• Seasonal goods

What’s important to the merchant?

• Product availability

• Profitability

• Loss leaders

• Products becoming obsolete/expiring

• Rules about Licensed content and/or competing brands

How the Right ESP Makes a DifferenceHarnessing an enterprise email solutions toolfor dynamic recommendations, willenable you to:

• Integrate seamlessly: with the best-of-breed recommendations engines that use the most advanced techniques, (e.g., Apache Mahout framework);

• Scale dynamic recommendations: by building multiple dynamic content blocks to serve timely and smart product recommendations based on set targeting attributes via automated business rules; and,

•Optimizeonthefly:throughtestingandmeasuringspecificdynamicrecommendations to determine ‘champion’ elements (e.g., Dynamic Recommendation CTAs, and Layouts) and updating the business rules in real time to serve these winning elements.

Partnering with an enterprise email solution can also provide additional levers for building a best in class email program:

• Dynamic content blocks: presents truly custom targeted content based on set business rules and data attributes, (e.g., New Customer WelcomeOfferdynamicallyservedbasedonfirstpurchasedataandpreferences);

• Time of day feature: enables multiple versions of dynamic content to be presented based on the time of day an email is opened; and,

• Real time weather feature: produces timely and relevant dynamic content based on current and/or forecasted weather segmented by zip code or geographical business rules.

pg. 6

Balance is KeySo, there are a lot of options of how to apply dynamic recommendations.

Sometimes it may just be contextual from what is observed in a particular session on-line, e.g., a woman who has browsed men’s oxford shoes in an on-line session may receive a follow-up email presenting other options for men’s oxford shoes. Sometimes it may be more planned, for example: that same woman goes to a favorite website selling women’s fashions and is presented with options based on what she has purchased there in the past and what is relevant for the upcoming season. The best case may be balance. For example, using historical information to present suggestions of what that person may want (e.g., “Similar products” – which frequently appears in a category of recommendations of “People who bought, also bought” (PWBAB)); additionally, providing recommendations based on contextual clues (e.g., “Best Sellers” – you just looked at a handbag, here are our most popular handbags that we’re selling right now). When developing communication strategies for clients, we look at 5 categories of communications to determine a company’s approach, strengths, and opportunities for helping improve, or implement, dynamic recommendations. The categories: 1. Lifecycle communications – these include those focused on the initial communications

in a relationship, for example: Welcome Series and Activation programs and those at the end (or potential end) of a relationship, e.g., Reactivation and Win-back programs.

2. Base communications – these may include communications about things like: seasonal promotions, monthly newsletters, store openings, new products, engagement objectives, and other forms of content delivery.

3. Purchase cycle – those communications tied to a direct purchase activity, these may include:browsing,abandonedcart,orderconfirmation,purchasereceipt,packingslip,purchase survey, product review, information about the product purchased, and request for repeat purchase.

4. Events or behaviors – many of these communications may be considered triggers and include things that may be timed, for example birthdays and relationship anniversaries, in addition to other non-timed events like moving, having children and getting married.

5. Loyalty program – these have their own eco-systems, which include communications for: awareness building; enrollment; activation; status and account reporting; threshold and promotional incentives; and reactivation.


There are many additional examples of marketers using dynamic recommendations. So why aren’tmoremarketersusingthistool?Ittakesathoughtful,coordinatedeffortacrossanumberof disciplines – which is a challenge for many.

Framework for Dynamic Recommendations

Welcome and activationRe-activationWin-back

PromotionsNewsletterNew productsStore opening

Abandon browse and cartOrder confirmationShip confirmationPurchase receiptOrder follow-up

BirthdayNew moverProduct obsolescence

Enrollment recruitmentMembership kitActivationRedemptionStatusThresholdRe-activation

Communication types include

Best dynamic recommendation options

Channel types

Lifecycle

Base

Purchase cycle

Events

Loyaltyprogram

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Where to focus with recommendations?

Browse/click, but didn’t buyA couple of things to focus on here: the actual item and “Similar Products” to what was viewed, and other “Best Sellers” (in case the shopper decided they didn’t want what they found).

Abandoned cartSimilar to the prior point, there may be a number of reasons for the abandonment, so recommend a couple of types of products orvariations,(e.g.,theydidn’tfindtheexactcolor they wanted).

Order confirmation, receipt, shipping confirmation, and post-purchase communicationsHere we’d suggest focusing on/testing three types of recommendations, the “What’s Next”, “Similar Products” as well as the “People Who Bought also Bought.” The latter is a form of tacit recommendation, which many people findcomforting.

The reason? These are the touch-points and times when a customer is most likely to buy, so for the marketer it is the easiest time to stimulate an incremental purchase…be it an incremental order or an additional item in the basket.

pg. 8

A Structured ApproachWhen speaking with marketers, we use a framework called “Diagnose to Deploy”, or D2D to describethetypeofeffortrequired. 1. Diagnose. Work needs to be done to understand current marketing and merchandising

activitiesandthepotentialbenefitsofdynamicrecommendations.Thismayincludethinking about options for which audiences to focus on (e.g. from segment-level to individual-level)totheitemstoincludeandthebenefitstobeexpected.Thistypicallyis where goals are established and performance measures, targets, and initial reporting requirementsaredefined.

2. Define. Thisisdefiningthecommunicationsexperiencesandcampaignsandwhereandhowdynamicrecommendationscanbeusedtoachievemarketingbenefits.Thiswillincludedefiningtherolesandresponsibilitiesacrossthefunctionalgroups(e.g.,Marketingand Merchandising) and the channel managers (e.g., ensuring consistency across e-com, email,andstore).Italsorequiresconsiderationofthedigitalassetsnecessaryfordifferentoptions(e.g.,doesacompanywith100,000SKUswanttoincludeallinitsdynamicrecommendations), and the processes necessary for capturing, using and maintaining the rightassets.Italsowillincludedefininghowmanyitemsandwhattypesshouldbepresentedatdifferentcommunicationspoints.Forexample,onanabandonedcartemail,shouldsimilarproductsberecommended,orbestsellersinothercategories…or2ofeach?

3. Design. Determining how dynamic recommendations will be presented to customers. This isanareawherethereneedstobeanactiveinteractionwiththeDefineactivitiesbecausemany options are available. For example, building on the example from the prior point, in an abandoned cart email, it may be possible to have a great user experience design for an email onaworkstationthatpresents10recommendeditems,butinaresponsivedesignedemailfora mobile device, it may be better to present only a few.

4. Develop. Here is where technology needs to be acquired and set-up (e.g., the selection and implementation of recommendation engines like IBM’s Interact, Certona, Baynote), operational business rules are established, and automated interfaces are created to feed the decision-making and recommendations. Additionally, activities are necessary to create the user interfaces for the presentation of the recommendations, e.g., tagging sites, modifying e-com web interfaces, modifying POS interfaces, creating new email templates and new order confirmations.

5. Deploy. This is where the operations occur. This includes keeping the business rules up-to-date and revising as the business changes and new items come and go. It also includes monitoring APIs and other interfaces to make sure that feeds operate properly and the recommendations are properly presented across the range of touch points and wide range of options.

Back to the first D! Here is where measurement and reporting occurs and options for tuning and refinementaredetermined.

Diagnose

Define

DesignDevelop

Deploy


Components to manage when implementing dynamic recommendationsThere are three key components to be managed during implementation or expansion of dynamic recommendations: 1. Control – Marketers and merchandisers each will need to give up some control. They

will need to trust the technology of automated decision-making and recommenders. It’s difficultformanytodo,butit’sessentialforanysignificantbusinesstoscale.Anycompanywith millions of customers and tens of thousands of items must have automation to make recommendations to those customers. The same is true for companies with far fewer customers and products. The risks can be managed. The recommendations may not always be perfect, but they can be set-up so they don’t have negative consequences (e.g., products considered to be risqué can be suppressed from being served in some cases).

2. Optimization – There is a whole new range of things to consider, because so much more is possible.Thereshouldbespecificidentificationofareastobeoptimizedandaprocessfordeploying, evaluating, and incorporating results from tests.

3. Customer Experience – Many touch points may need to be altered but the implications are profound. What’s possible is the presentation of highly relevant content at a much higher percentage of touch points. The outcome…higher engagement with the company, more salesandprofit.

Use automation to optimize

Increase touch point quality and quantityto enhance the customer experience

Technology &Automation

Marketers& Merchants

AddControl

RemoveControl

pg.10

Our RecommendationsTherearefivekeytakeawaystorememberwhenimplementingdynamicrecommendations:

1. Do something. Customers are expecting this type of interaction from marketers and if you doitrightitwillpayoff.

2. Pick a single communications category to start. We mention 5 in this document…choose one,defineclearperformanceobjectives,andgoforit.

3. Do something you can prove by testing.Definesomethingyou’llbeabletomeasuretheincremental value from. For example, the average number of items in a basket (or even less direct measures like page views, and dwell times).

4. Plan for something you’ll trust. There are certain things that you (and other stakeholders in your organization) will trust; begin with those. See our sidebar for suggestions of where to start.

5. Know that those who will do this right will win! Customers willingly accept relevant recommendations and many are prone to act on impulse purchase opportunities. Those who make it easy for customers to have a higher percentage of their spending at their store will defeat those who do not. It’s becoming increasingly more popular and easy to do, so there’s no doubt that there will be winners and losers.

Dosomething!

Pickcategory

Prove withtesting

Plan Win


How Yes Lifecycle Marketing helps clients implement dynamic recommendationsNot surprisingly, we leverage our own framework of “Diagnose to Deploy”, or D2D to help clients build, implement and optimize dynamic recommendations:

1. Diagnose. We collaborate to understand current marketing and merchandising activities andthepotentialbenefits.Thismayincludethinkingaboutoptionsforwhichaudiencesto focus on (e.g. from segment-level to individual-level) to the items to include and the benefitstobeexpected.Thistypicallyiswheregoalsareestablishedandperformancemeasures,targets,andinitialreportingrequirementsaredefined.Wealsowillmonitorprograms and report and analyze results to help with optimization.

2. Define. We document experience maps and customer journeys and campaigns and where andhowdynamicrecommendationscanbeusedtoachievemarketingbenefits.Wealsohelpclientsdefinetherolesandresponsibilitiesacrossthefunctionsandthechannelstodevelop and maintain dynamic recommendations.

Italsowillincludedefininghowmanyitemsandwhattypesshouldbepresentedatdifferentcommunicationspoints;wecreatescenariostodeterminetherightapproachandalso develop implementation options.

3. Design.Thisisanareaforactiveinteraction,withthedefineactivitiestoconsider,optionsare available for presentation and messaging across the range of touch points. Also, here we determine approaches and processes for asset management.

4. Develop. We help clients select technology and also collaborate to determine set-up and operational requirements. This includes developing business rules, and automated interfaces to feed the decision-making and recommendations. Additionally, we can create user interfaces for the presentation of the recommendations, e.g., tagging sites, modifying e-com web interfaces, modifying POS interfaces, creating new email templates and transactional templates.

5. Deploy. We can operate systems for our clients keeping the business rules up-to-date and revising as the business changes and new items come and go.

While dynamic recommendations can seem like a daunting task to undertake, it doesn’t have to be. By developing your framework and staying in control of the process, you can develop a communication strategy that will help convert customers and create a lasting relationship.

Diagnose

Define

DesignDevelop

Deploy

[email protected] yeslifecyclemarketing.com