Christophet Nash at WebTomorrow about Creating Lifetime Customers Using Machine Learning and...

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Creating Lifetime Customers Using Machine Learning and Predictive Personalization

Creating Lifetime Customers Using Machine Learning and Predictive PersonalizationWEBTMRRW15 March 10, 2015Presented by // Chris Nash @chrisnashSenior business optimization consultant & Co-author Connect

Good morning. Today I am going to talk about the idea of using a combination of predictive technologies to create high-quality customer experiences experiences that aim to cultivate lifetime customers (customers who become so satisfied and loyal that they become customers for life).Now This event webtomorrow is of course an exploration about the question: what is the future of the web? We ask this question because we want to understand How can we all put ourselves in better position to be where the web is headed so that we can be in the right place at the right the time.Whats the future of the web? Its a big question. So I want to start by breaking that big question down to a smaller question. 12What happens in a web today minute?And that question is: what happens in one minute on the web?


Millions of customer experiences

Here is an infographic called data never sleeps. Its an attempt to quantify what happens on the web every minute.The stats are mind boggling. There are millions of social interactions, millions of personal interactions, millions of transactions, millions of business interactions.Summed up and this infographic does not cover all interactions : There are millions of customer experiences every minute. 34

But often low quality customer experiences

And while there are millions of customer experiences every minute, I think that many of us would agree that there are far too many low quality customer experiences.45

Dis-engagedMis-targetedDis-nurturedDisconnectedDis-customeredHow often have you experienced being Dis-engaged because you visit or revisit a website and the content you are presented with lacks relevancy with regard to your intent? (you need to spend too much time trying to find what you are looking for and the content your are presented with has little to do with what you need or are interested in)Mis-targeted by online advertisements that keep reappearing even after you booked that smartphone or bought that pair of shoes?Dis-nurtured - by receiving an email with content and calls to action that very broad and dont make sense given your relationship with the brand who is sending the email. We have a great deal on a hotel room in New York. (these offers are always about where you have been not where you are going)Disconnected because your customer experience is so different in different channels email, web, in store, and so onIn fact, too many times you may feel like you areDis-customer-ed by being treated like everyone else even though you are a loyal or regular customer.What to do 56What aboutthe web tomorrow minute?OK. That was the webtoday minuteWhat will happen in the web minute of tomorrow? Will the quantity of interactions increase while the quality of customer experiences remains low?What if you could increase the quality of the experience?6Accurately anticipatethe needs of customers in the moment based on predictive technologies #What if you could accurately anticipate the needs of customers in the moment based on predictive technologies?

The ultimate convenience, the ultimate in quality service, the ultimate customer experience What if as a seller you anticipate the needs based on a combination of behavior and big data analysis (based on what other similar customers need and do).

Research shows that Customer experience leaders out perform laggards by 76% 7Customers reveal digital preferences data as they make decisions in the momentCustomers seek relevancyBrands = experience architects Brands must create relevant experiences by anticipating next best actionCustomer experience Decision journeys #89Two Predictive TechnologiesPredictive PersonalizationMachine LearningRecognize in-the-moment behavior and behavior patternsBig data technology to analyze the past to predict the future


Persona ProfileProduct ProfileIn-the-moment, predictive personalization

webmobileemailsocialappscommerceAct on in-the-momentbehaviorProfile pattern matchProfile pattern match

Single view of individual customerExample: a potential customer for insurance . How can you identify needs and interests in the moment based on collective behavior?1011

Machine Learning Using Customer Experience DataUnstructured Customer Experience DataSynthesize DataTrain the SystemLearnPredictionsEvaluate & RefineProvidePredictive Data

APIAPIExamples to walk thru retailer on/offline wanting to predict next product; bank looking to offer loan or cc

1112What if you combine these two capabilities?1213

APIPredictive PersonalizationML Predictions1314PossibilitiesCommercePredict the next product to sell based on in-the-moment relevancy and cohort analysisOnline AdvertisingPredict the next online ad to display based on in-the-moment relevancy and cohort analysis

ContentPredict the next piece of content and call-to-action to present in the relevant channel

#Examples here141510 top bank in RussiaConsumer, Private, Commercial, Business bankingUses predictive personalization to increase sales of consumer loansBoosted conversion rate for completed consumer loan applications from 4% to 24% PS Bank

4% to 24%16Retirement savings fund2.1 million members; $75B assets Uses predictive personalization in combination with predictive data to increase member self-service and grow member satisfactionBoosted use of personalized online self-services conversions by 250% AustralianSuper

250%17Tips / TakeawaysDont: ask for marriage on the first date

Do: understand consumers basic drives universal human truthsSee: The Ultimate Marketing Machine350 CEOs, CMOs, and agency headssurveys of 10,000-plus marketers from 92 countriesHarvard Business Review JULYAUGUST 2014

#These marketers understand consumers basic drivessuch as the desire to achieve, to find a partner, and to nurture a childmotivations we call universal human truths.

The Ultimate Marketing Machine350 CEOs, CMOs, and agency headssurveys of 10,000-plus marketers from 92 countriesHarvard Business Review JULYAUGUST 2014

Avoid locking in customers with predictions

Dont ask for marriage on the first date

Include non-actions in predictive analysis

1718Tips / TakeawaysTake a phased approached to CX relevancyIf-then personalizationSimple data mergeAlgorithmpersonalizationSystemic algorithmpersonalizationMachine Learningpersonalization93% of companies using personalization experience sales increases*Econsultancy 2014#1819

OptimizeNurtureEngageInitiateRadiateAlignLifetimeCustomersAssess your organizations customer experience maturityTips / Takeaways#CTA Connect19

Take simple CXMM assessment

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