the strategic value of dynamic personalization

8/3/2019 The Strategic Value of Dynamic Personalization

1/21

Eric T. Peterson

Web Analytics Demystified, Inc.

www.webanalyticsdemystified.com

Sponsored by Baynote

www.baynote.com


2/21

The Strategic Value of Dynamic Personalization: A Baynote White Paper

2011 Baynote, Inc. All rights reserved. No part of this document may be 2

reproduced in any form without prior written permission of Baynote.

The definition of insanity is doing the same thing over and overagain but expecting different results.

- Usually attributed to Albert Einstein

Nearly every company known to the Senior Partners at WebAnalytics Demystified has had some kind of site, product or contentpersonalization effort in place for years. In some cases, millions ofdollars have been invested with few measurable results while thatmoney continues to be spent in the often elusive search for the one -to-one customer relationship.

More recently, this quest has been exacerbated by the explosion ofsocial media and the general belief that because we can now friend

and tweet our customers that we have somehow becomepersonally closer to them. We dont blame leadership for lookingcertainly we would like to have more relevant products and contentserved up when we visit our favorite sites but the available datasuggests that for the most part these efforts havent yet producedresults commensurate to expectations.

The logic required is relatively simple: you figure out what the sitevisitor is most likely to respond to and then put whatever that is infront of them during their visit. Unfortunately the devil is in the detailsand, in our experience, there are two undeniable truths about most

businesses relationship with digital consumers today:

1. Online interactions are largely unsatisfying;2. Efforts to optimize these interactions are largely ineffective.

While unsatisfying and ineffective may seem harsh, we challengereaders to critically examine their own content deployment and sitemanagement efforts. Most will find slow-moving processes governedby one or few peoples impressions of what the visitor is looking for.When their impressions are incorrect, conversion stays low,satisfaction stays low, and the business fails to take full advantage of

the digital opportunity.

Thankfully for marketers, merchandisers and business leaders asolution to both of these problems has emerged in the form of sitetesting and adaptation technologies. These solutions are allowingdigital marketers to leverage their audience to determine how tocreate optimized experiences online. By automatically determiningvisitor and customer preference based on measured engagement,

Many marketersare already reapclear benefits interms of higheronline sales, hig

conversion andhigher satisfact


3/21




the ideal combination of site elements can be determined and overallvisitor experiences can be improved.

Whats more, many marketers are doing this todayand are alreadyreaping clear benefits in terms of higher online sales, higher

conversion, and higher satisfaction. This white paper explores howExperience 2.0 and adaptive technologies are changing the rulesand allowing digital marketers and merchandisers to createincreasingly personalized digital relationships with their visitors,prospects, and customers.


4/21





5/21




Despite billions invested in site management and product presentmenttechnologies, one of the realities that marketing and e-commercemanagers live with today is that most sites fail to deliver highly satisfying

and highly profitable experiences. Consider:

U.S. information and communication technology investment willgrow to $758 billion in 2010 and an additional 6.6% in 20111;

U.S. interactive marketing spend will grow to $29 billion in 2010 andan additional 17% in 20112;

U.S. based investment in digital measurement technology will growto $514 million in 2010 and an additional 17% in 20113;

Fifty four percent of online retailers say in 2010 their conversionrates are up, although these sites reported average conversion rate

is only 2.9%

4

; Web Analytics Demystified estimates that less than 10% of budgetallocated to digital measurement efforts worldwide is money wellspent.

Billions are being spent every year on technology, marketing, andmeasurement yet the vast majority of companies have been unable tocreate successful and profitable outcomes online. While somecompanies certainly have made tangible improvements, most still have along way to go when it comes tocompeting effectively and efficiently in

digital channels. By recognizing that thecontinued reliance on the highest paidpersons opinion (HiPPO) will simplyreturn the same generally unsatisfyingresults, digital marketers need to begin tolook for viable alternatives.

Fortunately, alternatives exist, largely in the form of site testing andadaptation technologies and platforms. These solutions represent aprofound shift away from the status quoreliance on the decisions of thefew and instead leverage the behavior of current site visitors and

customers to determine the right combination of content, product, andsearch results likely to drive stated business outcomes.

1http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-172http://www.forrester.com/rb/Research/us_interactive_marketing_forecast,_2009_to_2014/q/id/47730/t/23http://www.forrester.com/rb/Research/us_web_analytics_forecast,_2008_to_2014/q/id/53629/t/24http://www.internetretailer.com/2010/10/29/cheery-forecast-retailers-expect-higher-holiday-web-sales

The continuedreliance on thehighest paid

persons opini(HiPPO) will sireturn the samgenerallyunsatisfyngresults.
http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17http://www.forrester.com/rb/Research/us_interactive_marketing_forecast,_2009_to_2014/q/id/47730/t/2http://www.forrester.com/rb/Research/us_interactive_marketing_forecast,_2009_to_2014/q/id/47730/t/2http://www.forrester.com/rb/Research/us_interactive_marketing_forecast,_2009_to_2014/q/id/47730/t/2http://www.forrester.com/rb/Research/us_web_analytics_forecast,_2008_to_2014/q/id/53629/t/2http://www.forrester.com/rb/Research/us_web_analytics_forecast,_2008_to_2014/q/id/53629/t/2http://www.forrester.com/rb/Research/us_web_analytics_forecast,_2008_to_2014/q/id/53629/t/2http://www.internetretailer.com/2010/10/29/cheery-forecast-retailers-expect-higher-holiday-web-saleshttp://www.internetretailer.com/2010/10/29/cheery-forecast-retailers-expect-higher-holiday-web-saleshttp://www.internetretailer.com/2010/10/29/cheery-forecast-retailers-expect-higher-holiday-web-saleshttp://www.internetretailer.com/2010/10/29/cheery-forecast-retailers-expect-higher-holiday-web-saleshttp://www.forrester.com/rb/Research/us_web_analytics_forecast,_2008_to_2014/q/id/53629/t/2http://www.forrester.com/rb/Research/us_interactive_marketing_forecast,_2009_to_2014/q/id/47730/t/2http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17http://www.forrester.com/rb/Research/us_and_global_it_market_outlook_q3/q/id/57256/t/2?src=RSS_2&cm_mmc=Forrester-_-RSS-_-Document-_-17


6/21




These technologies typically manifest in two groups, broadly defined bythe amount of input required to support the decision making process.The first group, site testing and optimization tools, are characterized bytheir ability to support and manage tests of the presentment andpresentation of site elements. By plugging in different variations in real-

time and monitoring visitor reaction, test managers and analysts are ableto make informed decisions about which combination of elements aremost likely to create satisfying experiences and drive businessoutcomes.

The latter group, broadly considered dynamic personalizationtechnologies, take the next logical step and remove the need for expertsto manage the entire merchandising process. Instead, these solutionsoptimize digital experiences in real-time by leveraging powerfulalgorithms designed to take advantage of the wisdom of the crowdsand collective intelligence. Thanks to the deployment of this technology,

companies around the world are starting to see tangible results,including:

Anthropologie has leveraged dynamic personalization technology todeliver a 35% increase in cross-sells, shifting this highly profitablesales category from 1% to 4% of total site sales;

The Stelter Company has leveraged the insights powered bycollective intelligence across 1,300 sites to dramatically improvetheir knowledge of which marketing efforts and content are leadingto high-value donations to nonprofits;

Intuit Payroll Services has leveraged these same algorithms toimprove customer self-service resolution rates to over 60%, closingin on the rates appreciated by phone-based service agents.

Given the reduced dependency on human resources to manage theoptimization process, adaptive solutions are seen by many as the logicalprecursor to the highly personalized digital relationships sought after bybusinesses and consumers alike.

And while the dynamic personalization technologies as they exist todaymay not be truly one-to-one, our belief at Web Analytics Demystified is

that the shift from a business-driven to a customer-driven merchandisingand content management strategy is a critical first step towards theultimate goal of highly personalized digital interactions.

The shift from abusiness-drivena customer-drivmerchandising contentmanagementstrategy is a crifirst step towardthe ultimate goahighly personaldigital interactio


7/21




While there are many ways to categorize the changing nature of content

and product presentation in digitally connected channels, at WebAnalytics Demystified we think in terms of experience and experienceoptimization. We do this for one reason: it puts the consumer squarelyin the center of the decision-making universe. By designing increasinglysophisticated and hopefully delightful experiences for the connectedconsumer, it is our belief that the desired business outcomes willlogically follow.

Furthermore, by thinking in terms of the kinds of experiences differenttechnologies and platforms are able to deliver, we are able to define acontinuum of experience optimization solutions. By clarifying the

strengths and limitations of each of these three categories, we are thenable to guide our clients towards the set of technologies most likely todeliver the desired results given financial considerations, resources, andtimelines.

Early on in the development of the Internet; experiences were largelystatic, designed by individuals, agencies, and managers based on theavailability of product and content and an often strongly-held beliefregarding what visitors would respond to. While this strategy wascertainly understandable given the available technology at the time, itwasnt long before business owners realized that there were oftenprofound differences between highly attractive and highly valuablesite designs.

Before long the wholly static approach to site design and presentationgave way to semi-static systems capable of some level of on the flymodification designed to try and personalize the visitors experience.Ranging from relatively simplistic dynamic HTML to more complexscenario-based content modification schemes, these semi-staticenvironments were largely rules-based and required a tremendousamount of advance planning.

Especially at the Enterprise-level, static and semi-static sites require atremendous investment in resources and human capital to effectivelymaintain and optimize the consumer relationship.

It wasnt longbefore businesowners realizedthat there wereoften profounddifferencesbetween highlattractiveandhighly valuablsite designs.


8/21




Whats more, the insights gained from the analysis of relatively staticsites is ultimately uninteresting. By treating your audience the same wayevery time they visit, the amount of knowledge you can collect is limitedand much the same as the definition of insanity often attributed to AlbertEinstein --- doing the same thing over and over again and expecting

different results. The creation of true knowledge requires active andcontrolled variation, something difficult to produce in even the mostsophisticated Experience 1.0 sites.

More recently, technologies have emerged from a wide range of vendorsdesigned to allow site operators to iteratively and algorithmicallydetermine the right combination of design elements, products, andmessages likely to deliver value back to the business. TheseExperience 2.0 technologies are essentially allowing site visitors

participation in determining how things should look and how the siteshould behave.

The technology powering the Experience 2.0 paradigm is largely builton powerful statistical models designed to take advantage of the wealthof visitor engagement data generated by every digital interaction. Bymodeling engagement in real-time, testing and dynamic personalizationtechnologies are able to present product and content alternatives thatare more likely to meet an individual visitors specific needs. Further,these alternatives can then be analyzed in meaningful ways such as bytaking a comparative measurement of engagement across multiple

audience populations seeing different messages.

For example, a leading provider of information about planned charitablegiving, using the dynamic personalization technology provided by thispapers sponsor Baynote, was able to dramatically improve levels ofengagement among high-potential value individuals researching oftencomplex charitable donation options. By leveraging data from like-minded individuals as an input into Baynotes collective intelligenceengine, The Stelter Company was able to produce insights that nearlydoubled engagement with content critical to the giving process. Givenan average planned gift of $50,000, the increased engagement creates

potentially dramatic financial impact for respected non-profits around theworld including Make-A-Wish Foundation, American DiabetesAssociation, CARE USA, and roughly 12,000 others.

The amount of investment required to create adaptive experiencesvaries widely owing to the two broad adaptation strategies deployed(described in detail in the next section.) Testing, while potentially lessexpensive given the availability of free tools, requires human resources

The insightsgained from theanalysis ofrelatively staticsites is

ultimatelyuninteresting.

By modelingengagement in time, testing anadaptivepersonalization

technologies arable to presentproduct and coalternatives thamore likely to man individualvisitors specifineeds.


9/21




able to plan, design, deploy, and analyze potential optimizations.Conversely, automatic adaptation has the potential to require more set-up time and can be more expensive relative to free solutions.

That said, at Web Analytics Demystified we strongly encourage our

clients to think about experience optimization notas a cost center for thebusiness, but rather as a potentially active profit center. Given the verynature of these technologies and their ability to calculate the netincrease associated with a particular change or set of changes,sophisticated business owners like eBay, Amazon, Dell, Expedia, Intuit,and others have long been using testing and dynamic personalizationsolutions to create and prove incremental revenue and operationalsavings back to the Enterprise.

We stronglyencourage ourclients to think

about experiencoptimization noa cost center fobusiness, but raas a potentiallyactive profit cen


10/21




The notion of dynamic personalization and adapted experiences that are

a reflection of consumer preference is nothing new. Direct marketershave been creating variations and adapting their outboundcommunication efforts for decades in an effort to create the optimalresponse in the target audience. In the digital space, A/B andmultivariate testing platforms have existed for years, although theiradoption has been somewhat slow, with Forrester Research estimatingmarket adoption at roughly 26%5. Newer adaptation platforms such asthe one provided by this papers sponsor Baynote have emerged morerecently and are beginning to gain critical adoption in a variety ofsectors.

Ultimately, Experience 2.0 technology exists to create more delightful,easier, and financially profitable interactions in digital channels.Regardless of whether your company chooses a more manualincremental testing strategy, a more automatic, algorithmic approach orsome combination of both, the shift to adaptive technology is a reflectionof the fact that your customers know themselves far better than you do.

Given the opportunity, your visitors and customers will alwayschoosethe easiest path, the most compelling offer, and the fastest resolution totheir problems if only you allow them. If you dont give them thischoice and instead persist in making essentially random changes to yoursites and applications, you will inevitably get exactly the same resultsyou have been getting all along: low conversion rates, poor satisfaction,and mediocre growth at best.

For companies willing to trust their visitors, customers, and increasinglyproven technologies, Experience 2.0 technology essentially comes intwo flavors: Expert-driven testing and optimization tools, and moreautomatically-driven adaptation platforms.

5http://www.forrester.com/rb/Research/online_testing_vendor_landscape/q/id/53637/t/2

The shift to

adaptivetechnology is areflection of thefact that yourcustomers knothemselves farbetter than you
http://www.forrester.com/rb/Research/online_testing_vendor_landscape/q/id/53637/t/2http://www.forrester.com/rb/Research/online_testing_vendor_landscape/q/id/53637/t/2http://www.forrester.com/rb/Research/online_testing_vendor_landscape/q/id/53637/t/2http://www.forrester.com/rb/Research/online_testing_vendor_landscape/q/id/53637/t/2


11/21




Multivariate and A/B testing technologies such as those provided bySiteSpect, Adobe, and Autonomy typically provide a robust suite of toolsthat allow the organization to manage and measure the incrementalvalue created by varying site content and presentation. Web AnalyticsDemystified has documented the process required to take full advantageof this approach at a high-level in our white paper with SiteSpect titledSuccessful Web Site Testing Practices6:

1. Testing project managers work with analysis, product, creative, andmarketingteams to determine what aspects of the site should be tested.

2. Analysts document the opportunity associated with testing, usually based onsome type of click-through or transactional analysis enabled via audiencesegmentation.

3. With the opportunity and effort sized, testing project managers typically submittest plans to management for approval to use necessary resources.

4. With permission in hand, content, marketing, Information Technology (I.T.), andquality assurance resources set about to create necessary variants to include inthe test;Assets are added to the testing platform, a test plan is created, and thetest will be started.

5. Tests will run for an indeterminate period of time, usually measured in days orweeks depending on traffic volume and success measures.

6http://www.webanalyticsdemystified.com/content/white-papers.asp
http://www.webanalyticsdemystified.com/content/white-papers.asphttp://www.webanalyticsdemystified.com/content/white-papers.asphttp://www.webanalyticsdemystified.com/content/white-papers.asphttp://www.webanalyticsdemystified.com/content/white-papers.asp


12/21




6. When tests complete, analysts set about evaluating the test to determine whichvariation produced the right combination of incremental value and brandconsistency.

7. Testing project managers present the recommended changes to management forapproval.

8. Management approves the recommendation and the changes are re-deployed

using the normal, I.T.-driven site deployment process.

When the business truly invests in testing as a competency, the processgets incrementally easier over time but testing is not easy. Therequirement for experts and analysts at multiple steps in this processcreates additional opportunities and risks. The opportunities manifestthrough valuable insights into visitor and customer behavior which, whenwell-documented, can be cascaded through the Enterprise toincrementally learn about the motivations and drivers that visitors arelikely to respond to.

The risks primarily manifest through the staffing and resourcerequirements associated with the end-to-end testing process. Simplyput, testing can be incredibly resource intensive --- on average,companies interviewed for this research were allocating roughly fourtimes as many resources to testing as they were to adaptive efforts.According to Max Perry, Director of E-Commerce and Web Developmentat Anthropologie, We could skimp on (testing) resources but we want todo it right. This requires a resource to own our testing platform,designers to create new content, and weekly testing meetings todetermine which campaigns we want to run.

Done right, you will need analysts, test project managers, and creativeand quality assurance resources commensurate to the amount of testingyou plan to do. And while many of these individuals already exist withinthe business and can be tasked with the creation of more content totest, the analytical and test management resources required are typicallydifficult to find, expensive, and often lacking the experience one wouldnormally associate with the high salaries they command.

Finally, while a well-run testing program can yield tremendous financialbenefits back the business, in many cases even the most exacting testsyield no results despite copious investments of time and effort, thus

transforming opportunity into opportunity cost. And despite WebAnalytics Demystifieds strong belief that every result --- financiallyprofitable or not --- is an opportunity to learn something new about asites audience, this perspective is often not shared by managersanxious to always see their testing investment pay off.

When the busintruly invests intesting as acompetency, thprocess getsincrementallyeasier over time

Testing can beincredibly resointensive - onaverage, compainterviewed for

research wereallocating rougfour times as mresources to teas they were toadaptive efforts


13/21




While enabling many of the same type of results as testing platforms, theadaptation platforms such as those provided by this papers sponsor

work to dramatically simplify the incremental improvement process byleveraging existing content and powerful algorithms. Rather than rely onindividual experts, automated systems leverage collective intelligenceand the wisdom of the crowds to determine which content, sort order,or specific results are likely to push like-minded visitors along in thesales or content discovery process.

While highly simplified, the general process looks like this:

1. Technology resources deploy adaptive web technologies across the site;

2. Business managers determine which site content, product pages and

search results are appropriate candidates for adaptation;3. Adaptation technology collects data, algorithmically determining audience

segments and monitoring for individual successes;

4. As new visitors visit, the technology groups each individual and;

5. Automatically changes content based on the previous response of similarindividuals;

6. As adapted sessions improve business outcomes, the algorithm is updatedin real-time and the process repeats.

This processcreates a continfeedbackmechanism thaable to respondquickly to chanin visitor behavthat wouldotherwise bedifficult to disco

(using traditionanalytics).


14/21




The key advantage of collective intelligence manifests most acutely instep three where technology models dozens of visitor interactions ---from mouse movements and clicks measuring engagement to referraland search data measuring intent --- and uses those interactions toautomatically create affinity-based segments. As new visitors arrive and

are categorized, the technology serves the most appropriate contentand the segment is then updated based on measurable outcomes. Thisprocess creates a continual feedback mechanism that is able to respondquickly to changes in visitor behavior that would otherwise be difficult todiscover (using traditional analytics).

The opportunity associated with these adaptive technologies is typicallyincreased sales and satisfaction metrics produced as the system is ableto optimize each individual visitor session. In many cases, with littleadditional modification of the site, this category of solutions is able toimprove product recommendations, content discovery, site search

results and otherwise optimize online experiences. Examples includeSun & Ski who leveraged Baynotes adaptive technology to automaticallymodify site search results to optimize product recommendations, yielding44% higher conversion rates and 28% higher average order value fromvisitors clicking on those recommendations7.

The challenges usually associated with adaptive technologies includecosts and implementation requirements. Some business owners areuncomfortable with this type of automated discovery and instead preferto maintain stricter controls over site changes and optimization. Thereare also limitations on what adaptive technologies are able to modify:specifically, current technologies are not designed to modify the lookand feel of the site, instead focusing on content, products, and searchresults, although these limitations are being resolved at an increasingpace as new vendors emerge and existing vendors evolve.

Finally, keep in mind that algorithmic systems are designed to improveover time and so you should not expect miracles right out of the box.Most companies interviewed for this report indicated that over timeadaptive systems delivered increasingly good results. Web AnalyticsDemystified recommends giving any Experience 2.0 technology at least12 months to prove its value to your business. By carefully trackingrelated costs and the incremental value delivered, you should have littletrouble deciding whether to renew your contract for subsequent years.

7http://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-

online-sales-at-sun-ski

With little additmodification ofsite, this categosolutions is ablimprove producrecommendatiocontent discovesite search resu

and otherwiseoptimize onlineexperiences.
http://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-skihttp://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-skihttp://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-skihttp://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-skihttp://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-skihttp://www.internetretailer.com/2010/04/01/follow-the-crowd-recommendations-boost-online-sales-at-sun-ski


15/21




Assuming your business is committed to incrementally improving thevisitor and customer experience on your site, the next step is todetermine which of these Experience 2.0 solutions is right for you.Each solution has its strengths and weaknesses:

Testing efforts require more human touch but even the mostrudimentary platforms impart the ability to test dramatic changes tosite design and presentation;

Adaptive platforms require less human intervention but are typicallylimited in the breadth of modification they are able to support.

The reality is that businesses working aggressively to create morevaluable and satisfying experiences on their site will likely need bothexperts and algorithms. Case-in-point: Intuit Payroll Services has

deployed both Baynote for dynamic personalization and Omniture fortesting. According to Matt Zybura, Group Manager for Online Help andSelf-Service at Intuit Payroll Services, testing complements theiradaptive efforts, especially when working to determine user thresholdsfor navigational elements. At Intuit, like nearly all of the companiesinterviewed for this research, testing is a component of individualprojects whereas collective intelligence is an integrated component offinal, delivered products.

The best advice Web Analytics Demystified can give is to choose onestrategy and give it a reasonable chance to succeed, asking where

should we start not which should we choose. To help make thisdecision, we have created the following consideration matrix:

Desire or Limitation Consider

Rapid deployment with minimal set-up Dynamic Personalization

Optimization of product sort, selection, or search Dynamic Personalization

Limited resources to manage adaptation efforts Dynamic Personalization

Limited time to show results internally Dynamic Personalization

Require statistical analysis of options Either

Optimization of broad site design, including navigationalelements Testing

Optimization of specific functionality, including shopping cartand product configuration applications

Testing

Require detailed analysis of decision making process granularto the level of test and combination

Testing

Limited internal tolerance for moderately complicatedmathematics/modeling as part of decision making process

Dynamic/Neither

Businessesworkingaggressively tcreate morevaluable andsatisfyingexperiences otheir site will lineed both expand algorithms


16/21




As noted, we believe a high functioning Experience 2.0 organizationwill ultimately need both testing and dynamic personalization technology.The reason Web Analytics Demystified recommends carefully decidingwhere to start is that, in our experience, the best way to generate

internal consensus to evolve site experiences is to change behaviorsthat contribute to top-line or bottom-line financial results. Especially inresource constrained or highly competitive situations, the faster thebusiness is able to tell a story about the value of site adaptation, themore likely leadership will be to commit additional resources toadaptation projects.

Readers considering the deployment of adaptive technologies in aneffort to make the shift to Experience 2.0 should consider the followingexamples. We hope that our effort to clarify resource requirements, timeto deployment, and time to value will help you sell the potential strategicvalue of these solutions within your organization. Our decision tohighlight examples associated primarily with automatic and algorithmicsolutions is a function of this papers sponsorship and the author ishappy to provide other examples upon request.

Retailer Anthropologie is intensely focused on creating a unique buyingexperience for their female clientele regardless of the buying channel.Their web site is highly stylized, self-described as a one-of-a-kind andcompelling shopping experience that makes women feel beautiful,hopeful, and connected. The challenge, of course, in online retail issimultaneously creating a highly stylized yet effective sales environment,and doing that in a scalable and sustainable way.

To this point, Anthropologie had been manually cross-promotingproducts based on merchandiser knowledge, a time consuming and not

always effective strategy for exposing related products during theshopping process. The company turned to Baynote and theircompetitors to alleviate this manual requirement and eventually selectedBaynote based on the companys ability to power cross-sell as well astheir support for A/B testing to prove the effectiveness of their platform.

Initially our merchandisers had concerns about turning our cross-saleefforts over to an algorithm, says Max Perry, Web Development Director

Initially ourmerchandisersconcerns abouturning our crosale efforts ove

an algorithm Once we saw thresults Baynoteable to deliver, concernsdisappeared.


17/21




at Anthropologie. That said, once we saw the results Baynote was ableto deliver, those concerns disappeared and now we are looking toexpand our use of collective intelligence into both site search and emailmarketing efforts.

What then were their results?

In early testing, Baynote-influenced buying sessions saw a 35%increase in the number of cross-sell products sold;

Cross-sell product views have increased from 2% of total productviews (pre-Baynote) to an average of 7% of total product views;

Since deploying their dynamic personalization platform, Baynote-influenced cross-sales have increased from 1% to 4% of total sitesales.

More recent results have found that Baynote has helped Anthropologie

drive 57% more cross-sell clicksand 50% more cross-sold onlinedemand revenuewhen compared to sales not assisted by Baynotestechnology --- impressive no matter how you slice it.

Given a four-week deployment time and the fact that the solutionpractically runs itself, we are very happy with our investment in Baynote,says Mr. Perry. The combination of our core merchandiser knowledgeof product and customer, combined with Baynotes ability to determinesubtle shifts in consumer engagement, delivers performance superior toone or the other alone. At this point Baynote is integral to howAnthropologie sells in the online world.

The Stelter Company is a leading provider of marketing services fornonprofits focused on planned giving. While less than 10% ofAmericans leave money to a charity after their death, the size of a typicalplanned gift makes this donation path incredibly important to charitiesand other nonprofits. Unfortunately, information describing the benefitsand requirements for planned donations is perhaps the ultimate in long -tail content -- incredibly important to site visitors considering such a gift

and otherwise invisible.

The nature of planned giving creates a unique challenge for nonprofits --- very little can be learned about visitors researching the topic on a givensite. The numbers are just too small, even in the largest charity, saysBev Hutney, Director of Innovation and Research at The StelterCompany. We use Webtrends for some web analytic data but its justnot helpful since it measures popularity of content and the stuff we are

The combinatioof our coremerchandiserknowledge ofproduct andcustomer, combwith Baynotes ato determine sushifts in consum

engagement, deperformancesuperior to one the otheralone.


18/21




doing is unpopular unless you are the one individual cons ideringleaving $1,000,000 to charity when you die.

The solution, which is perhaps the most innovative use of adaptivetechnology ever described to Web Analytics Demystified, was to deploy

Baynote across all 1,300 of Stelters customer sites, essentially creatinga huge collective of intelligence on the topic of planned giving. BecauseStelter has content editors who are actively mining engagement dataprovided by Baynote, the company is better able to makerecommendations about which content is most likely to be compelling toany of the sites in their network.

Recommendations are one of the key differentiators between us andour competitors, says Mrs. Hutney. Because we can quantifyengagement we can determine how on-target our messages are andthat is hugely valuable to the business. Whats more, because the

planned donation cycle is long, making it difficult to measure the financialsuccess of their dynamic personalization efforts, Baynote has helpedStelter:

Increase page views per session by nearly 90%, a fundamentalimprovement demonstrating that Stelters approach is deliveringappropriate content in the right context;

Increase engagement time per session by over 85%, a criticalmeasure given the involved nature of the content, driven by thecontent-level insights Baynote is able to provide.

While set-up was somewhat involved --- Baynote needed to ensure thatcontent designed for the Make-A-Wish Foundation wouldnt suddenlyappear on CARE USAs web site --- once deployed and validated thetechnology requires almost no additional input on an ongoing basis. Weare a small company, says Mrs. Hutney, With 75 people, 30 of whomare dedicated to creating marketing materials for both online and offlinechannels, we needed to have a system that ran itself. That is the beautyof Baynote we dont have to do any analysis: Baynote does it for us.

Whats more, the insights derived from Stelters collective intelligenceefforts are helping optimize the companys direct marketing efforts in

traditional channels. According to Mrs. Hutney, When we learn that apiece of content is compelling or another is off-putting, we areimmediately able to roll those insights into our direct mailing, a strategythat has been shown to generate a measurably better response thanother historical efforts.

Recommendatare one of the kdifferentiatorsbetween us andcompetitors

The insights defrom Stelterscollectiveintelligence effoare helping optithe companys dmarketing effort

traditional chan


19/21




For more than 25 years, Intuit has helped small businesses managetheir business and finances, an incredibly complex process as any

business owner will attest. Many customers struggle with thecomplexities of payroll language, a challenge further complicated by thesensitive nature of payroll --- the average employee doesnt want to hearthat their paycheck is late because the boss couldnt figure out a piece ofsoftware.

Customers were coming to us and saying I need your help and you aremaking it harder than necessary to find answers, says Matt Zybura,Group Manager for Online Help and Self-Service at Payroll Services.We had been trying to figure out internally what the best answer toserve was, which, in retrospect turned out to be a horrible, painstaking

process.

With thousands of answers in their system, Zybura needed a betterstrategy to surface answers and turned to Baynote. Applied to customersupport, collective intelligence allows customers to select the categorythey are interested in and Baynote does the rest. Whats more, becausethere are inevitably answers that Intuit would prefer to answer on thephone, Zybura is using Baynote to funnel customers towards the rightchannel, further improving customer satisfaction.

Evidence that this is working for Intuit?

Interaction rates with customer support content have increased bymore than 25%;

Issue resolution rates are over 60%, in some cases exceeding 70%for months at a time nearing resolution rates appreciated byhuman operators at Intuit;

Mr. Zyburas relatively small team is able to support over 1,000,000Payroll Services customers.

Perhaps most important, because Baynote has effectively resolved theinternal debate about which answers to serve given a specific question,

Mr. Zyburas team is able to focus on other, potentially higher valueaspects of the customer experience. Before Baynote, we wereoftentimes just chasing answers and wasting time. Now we are ablefocus our internal efforts on making the entire support process easierand developing new ways of encouraging customers to self-serviceanswers.

Now we are abfocus our internefforts on makinentire support

process easier adeveloping newof encouragingcustomers to seservice answers


20/21




If you have been working diligently to improve the quality of your onlinechannel and deliver more engaging digital experiences, we sincerelyhope this research was useful. Ideally our description of the shift

towards Experience 2.0 has informed you about both the nuances ofthe technology involved and the opportunity presented to your businessand your audience. Especially if your efforts to substantially improveyour results have become frustrating, we hope you are now seriouslyconsidering an investment in either testing or dynamic personalization ---or both!

Naysayers may make the case that this technology is new and relativelyuntested but that is not the reality. The fundamental underpinnings ofboth types of Experience 2.0 technologies have been around fordecades and have been proven in some of the most financially sound,

highly visited, and best known destinations on the Internet. Furthermore,the statistical methodologies powering Experience 2.0 are as old as thescientific method itself.

If your web site or web-based business is stuck in a rut, if yourdevelopment and deployment cycles are measured in months or years,or if your key success metrics stalled out once the low-hanging fruit waspicked from the tree, consider Experience 2.0. Vendors like Baynoteand their worthy competitors have become well versed in demonstratingthe value their technology can provide, minimizing deployment times andto the extent possible, the resource requirements to allow businesses to

explore new ways of improving relationships with online visitors.

Perhaps its time for you to join Anthropologie, Intuit Payroll Services andThe Stelter Company and have an Experience 2.0 success story of yourown to tell.

The authors welcome your comments on this research.

Eric T. Peterson, CEO and Principal Consultant at Web Analytics

Demystified, has worked in web analytics since the late 1990's in avariety of roles including practitioner, consultant, and analyst for severalmarket-leading companies. He is the author of three best-selling bookson the subject, Web Analytics Demyst ified, Web Site MeasurementHacks, and The Big Book of Key Performance Indicators , as well asone of the most popular web analytics bloggers atwww.webanalyticsdemystified.com.

If your web site oweb-based businis stuck in a rut, your developmeand deployment

cycles are measin months or yeaor if your keysuccess metricsstalled out once low-hanging fruiwas picked fromtree, considerExperience 2.0.
http://www.webanalyticsdemystified.com/http://www.webanalyticsdemystified.com/http://www.webanalyticsdemystified.com/


21/21


2011 Baynote Inc All rights reserved No part of this document may be 21

Mr. Peterson has committed much of his life to the betterment of the webanalytics community, so much so that Jim Sterne, President and co-founder of the Web Analytics Association says "Eric's leadership in theindustry in unparalleled, his devotion to the community is legendary, andhis years of experience translate immediately into strategic and tactical

competitive advantage for everybody who works with him."

Web Analytics Demystified, founded in 2007 by internationally knownauthor and former Jupiter Research Analyst, Eric T. Peterson, providesobjective strategic guidance to companies striving to realize the fullpotential of their investment in web analytics. By bridging the gapbetween measurement technology and business strategy, Web AnalyticsDemystified has provided guidance to hundreds of companies aroundthe world, including many of the best known retailers, financial servicesinstitutions and media properties on the Internet.

For more information on Eric T. Peterson and Web AnalyticsDemystified, please visit www.webanalyticsdemystified.com.

Baynote enables dynamic personalization, a customer experience that isalways personal, relevant and convenient. By observing engagementpatterns among like-minded individuals to understand user intent, theBaynote Adaptive Web Suite automatically optimizes and adapts theonline experience, leading to increased conversions, revenue andloyalty. Baynotes customers include: AT&T, Dell, Sun & Ski, Expedia,

Intuit, Urban Outfitters and J. Crew. The company is based in San Jose,CA, with additional offices in the U.K. and Germany.

the strategic value of dynamic personalization

Documents