Breaking the Adobe Addiction: Using Celebrus & Aster for Better Web Analytics/ Personalization

Transcription

1 Breaking the Adobe Addiction: Using Celebrus & Aster for Better Web Analytics/ Personalization John Hines & Stewart Hanna Director, Corp Marketing Services - Digital Teradata Sr. Sales and Business Development Celebrus Technologies

2 At Teradata, we believe Analytics and data unleash the potential of great companies

3 Challenging the old way of handling Web analytics and personalization Proposed Solution: Celebrus + Teradata + Teradata Aster Examples of Teradata Aster n-path Analyses Personalization Deep Dive: Business Case for Teradata Solution Architecture 3

4 The Old Way Millions of visitors come to our digital sites

5 The Old Way and everyone sees the same home page/sub-pages Same banners, same headlines, same ads

6 The Old Way Then we report on their movements/totals as snapshots, in aggregate, based on Adobe server-side tagging on every page Same banners, same headlines, same ads

7 Which We Turn into Slides

8 Problems with This Approach: No prediction of cause and effect No same-user tracking over multiple visits No statistically valid pathing models that could be easily read/understood, at an individual level (why did this person become a lead?) Kept us anchored to Adobe (formerly Omniture) for all web analytics! (translation: EXPENSIVE) Adobe Server-side Tagging is laborious, even with ATM/DTM Adobe Target code was heavy on our page for Personalization (added 6-8 seconds to home page load times)

9 The Time Had Come for Personalization of T.com and Advanced Analytics Personalization is a recognized key trend of modern web sites

10 Technology of Choice: Celebrus High performance streaming event capture & delivery platform Providing on the fly contextualisation to digital data from multiple sources delivering to multiple targets Tagging-free deployment is simpler to use & more effective than Adobe Target Provides more detailed & complete website big data than Google Analytics & Adobe Analytics/SiteCatalyst Gives us a much deeper, contextual understanding of individuals through: In-memory view of each user's interactions in their current website session Historic customer profile with behavioural data from previous sessions This deeper understanding helps us optimize which actions & messages to take when: Personalizing website content for each individual user in real-time Sending messages to external systems Celebrus is the #1 Teradata partner for customer-level digital interaction data capture & management Celebrus captures data from 15bn digital visitors on over 30,000 websites per annum

11 4 Business Cases for using Celebrus and Teradata Aster 1. Optimize Golden Paths (increased site conversion) 2. Attach web history and pathing to leads for Inside Sales(Increased lead close rate) 3. Provide personalized experiences (increased conversion) 4. Remove non-performing terms from our agencies paid search buys, with little negative impact on conversion levels (Increased paid search efficiency) 5. Apply Marketing Attribution models to activity data which includes web (advanced analytics) 11 > 9/11/2016 Truly enables marketing to use big data to drive our digital experience!

12 A View of Celebrus Delivery of the data file to Celebrus can be scheduled and placed on the Celebrus server Captures all paths over multiple sessions from both anonymous /known 2016 Teradata visitors; data automatically feeds analytics/personalization rules engine

13 Celebrus Considerations Celebrus can deliver incredibly rich and detailed data which has some great advantages: Power analytics to uncover previously hidden insight Much easier to get detailed data than by tagging Celebrus data has business context applied so it so has far more value than clickstream data Also captures from web and mobile apps as well as across devices enabling complete single customer view You do near to bear in mind however: That can create a lot of data to store You might have to spend some time understanding which data is more valuable and filtering out the "noise" In order to identify activities at a company level an add-on package, Maxmind, was needed to provide geo-location insight - they are a Celebrus partner and very inexpensive

14 The Right First Step: Connect the Source IDW Data to Celebrus Business team uses the self-service data warehouse environment (using BusinessObjects) to develop the Celebrus web analytics data file 2016 Teradata Web team can pull analytics at any time on any of ~500 attributes!

15 Celebrus-powered Aster npath Analysis: A path that seems to be working well 1. Optimize For marketing.t.com, shows most successful paths to Request a demo. Two main sources of traffic: t.com homepage and marketing.t.com homepage. Paths seem to be working, as the majority are going where we would expect

16 Compared to a Much More Complex Path Here are paths to the download of our 2 nd -most popular asset in October, the Data Lake white paper. Shows no clear path and a fairly confusing experience this presents an opportunity for digital to optimize and increase clear visibility for this strong asset! A new model for how digital looks at our web presence.

17 Aster Reveals Another Opportunity to Increase Responses Shows that some people are finding their way from the Webcasts page in the Resource Library and the bigdata.t.com homepage to the Forbes survey page (our most-downloaded asset in Oct). If we featured the Forbes Survey more prominently on those pages, we could simplify their journey

18 Future Test npath Cases: Other Events/Scenarios of Interest Customer Journey Map Account heat map insights Patterns of key pages/site items Which pages are truly performing best? Pages with most activity, compared to bounce rates/ Marketing Qualified Response success rate Patterns based on profile of person who filled out MQR forms (tied to EDW) Patterns based on customer journey time/# of visits Shorten the time from 1 st visit to Marketing Qualified Response Tie to SAM data so paths for specific sales-qualified leads can be analyzedwhich paths made the most money for Teradata? 2016 Teradata #bigdata #teradata

19 Personalization: Business Impact for Teradata Top-Level Business Impact Goals: Increase page-level click-through rates by 20% Increase % of engaged visits from 45.8% of total visits (2015) to 50% of total visits Increase site conversion rate of Marketing Qualified Responses (MQRs)/Visits from 1.24% (2015) to at least 1.50% Increase % of MQRs which come from Target Accounts from 32% (Jan-May 2016) to 50% We are being more conservative, but will estimate 10-20% improvement in engagement and conversion (extremely dependent on campaign-specific goals, content, and design

20 The Elusive Question for Digital Marketers in 2016: Which is Most Effective for Personalization? Anonymous Visitors Account/Company Name Industry Previous Anonymous Online Behavior Account Stage in Waterfall (we know the company, so we can tie to our Account DB) New vs. Return Visitors Referral Source (search term used, referral site) Known Visitors (had visited previously and given us contact info) Job Title/Role Previous known user behavior, post-form fill out (attendance at last year s PARTNERS, specific white papers downloaded, campaign forms filled out, etc.) Individual Name (ex.: welcome back, Samantha ) No one can answer that question today - We will!

21 Degrees of Personalization Behavioral or A/B Personalization past browsing behavior A/B tests Account Attribute Personalization We might not know exactly who you are, but we know and really care about your company Web Visitor Contact Attribute Personalization You ve filled out a form or signed into our website. Now we know precisely who you are and can treat you uniquely based on your contact or account profile.

22 Personalization Proof of Concept Tests ~8 week POC engagement, followed by project readout and production readiness and training Behavioral or A/B Personalization A/B Test Welcome Back Message We see you ve visited another one of our sites Account Attribute Personalization Industry-specific messaging Web Visitor Contact Attribute Personalization Business Level-specific messaging Business Function-specific messaging Volume test of 100K contacts

23 Personalization Architecture for Account and Individual Level Historical Browsing Behavior Teradata Data Warehouse (dev) MaxMind to Account Mapping CRM Account Attributes CRM Contact Attributes Visitor Celebrus Personalization Server Real-time collection and personalization teradata.com Celebrus Behavior/Collection Server Real time Batch

24 Simple to Complex Test Cases for Personalization on Dev Crawl Celebrus developed initial configuration, with TCOM in supporting role Use Case: A/B testing Show Celebrus capabilities for delivering A/B testing of different pieces of content 2016 Teradata

25 Simple to Complex Test Cases for Personalization on Dev Crawl Celebrus developed initial configuration with TCOM in supporting role Use Case: Returning visitor Show different content to returning visitors >> You saw x last time here is y 2016 Teradata

26 The Biggest Challenge Celebrus/MaxMind captures and stores visitor information for anonymous personalization MaxMind Wal-Mart U.S. secret sauce Teradata Account List Account Nbr 1234 IT EDW team had to figure out how to connect Maxmind s company ID to Teradata s Account Number Enables us to personalize on any attribute in Teradata EDW

27 Mapping Our Account Attributes to Celebrus Celebrus feed captures activity; when Company/Industry uploaded into Celebrus with creative assets, different industry messages shown to visitors from those specific companies Account # and Industry matched to companies in Celebrus/Maxmind 2016 Teradata

28 Specific Messages for Visitors from a Single Company Walk TCOM started to build experience around configuration Use Case: Account-based content Create campaigns based on the user s organization, determined by Maxmind. e.g., Add or remove content based on IP>> Ability to show a single company a customized message 2016 Teradata

29 What do We Use to Allow Web Visitors to Self- Identify? Forms on T.com: Contact Us, Resource Library download form, Bigdata.t.com forms, webinar forms take most recently updated contact data to use for personalization attributes 2016 Teradata

30 Loading Individual Attributes into Celebrus Table created with addresses matched to items we might want to use for personalization scenarios Uploaded into Celebrus with creative options; when user attached to that comes back, they see custom messages 2016 Teradata

31 Personalization Enablers/Vulnerabilities Behavioral or A/B Personalization Enablers Celebrus Software Vulnerabilities Susceptible to cookie clearing, Celebrus is a 1 st Party Cookie Improve Teradata web page artifact labeling Account Attribute Personalization Celebrus /MaxMind Software Requires MaxMind to SAM Mapping (manual) Data warehouse to supply SAM account attributes to Celebrus Susceptible to Internet connection (ip addres) identification Web Visitor Contact Attribute Personalization Celebrus Software Requires visitor identify via form fill out, or Tpass login Data warehouse to provide SAM contact attributes to Celebrus Susceptible to cookie clearing, Celebrus is a 1 st Party Cookie Contact data quality

32 Specific Post-POC Use Cases for Personalization Basic/Behavioral Messages Welcome Back to returning visitors Specific A/B banner testing (many, various) Industry-Specific Banners When visitors come from companies within specifically identified industries, they should see banners on any page where they arrive which specifically target their industry with industry-specific offers Personalized Messaging for Target Accounts/Individuals Show 1 st visit messaging determined to be appropriate for specific account (s) Or, after 2 nd visit, they see messaging based on their previous on-site activity If they have filled out a form, and we have contact information, possibly welcome by name Offer to have them return to where they left off Show them relevant product- or solution-related content based on their job title/function You Might Also Like Asset Suggestions for Target Accounts Create a widget that shows on target pages (being determined) with a list of recommended assets, based on visitor attributes Pages Viewed By Your Peers Widget for Target Accounts Create a widget that shows the top pages viewed by other people from their company domain, or by other people with their similar job title from other companies Could be modified to show top assets downloaded by other people from their company or job title

33 Conclusions What isn t seen on any of these slides is Adobe Teradata can now perform detailed pathing analytics and deeper personalization than that offered (to date) by companies like Adobe, DemandBase, Google, and LinkedIn A repeatable process involving cooperation between Marketing and IT Biggest challenges ahead: data quality and content creation strategy We can help you do exactly the same thing talk with us about your web data situation Our addiction to Adobe and Google has been broken!

34 At Teradata We empower companies to achieve high-impact business outcomes through analytics at scale on an agile data foundation

35 Thank You Questions/Comments and Follow Me JohnHineseComm Rate This Session # 180 with the PARTNERS Mobile App Remember To Share Your Virtual Passes