Merging Web Analytics with Marketing to Increase Performance

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1 Merging Web Analytics with Marketing to Increase Performance Moderator: David Baker, VP Solutions, Avenue A Razorfish Panelists: Bill Nussey, CEO, Silverpop Jay Kulkarni, CEO, Theorem Margie Chiu, VP Strategy, Avenue A Razorfish

2 Over 56% of Marketing Executives said that the web was the HUB of their organizations marketing strategy, or it would become the hub, but only 15% say measuring results is a strength of their team 2006 WebTrends CMO Report

3 "Only 15% of the marketers state they have dedicated staff for web analytics and 9% have more than one, 15% have no staff and over 50% state it s a part-time role of one or more staff." 2006 WebTrends CMO Report

4 Only 15% of marketers are using click stream behavior data and an audience segmentation attribute Jupiter Research

5 " s based on web site click-stream data offer a three times to nine times revenue improvement over broadcast s." Jupiter Research

6 What we hope you ll get out of this session An idea of what technology decisions you ll be faced with in merging web data and Insight into this type of analytics and what it takes to manage it day-to-day Good ideas and examples of how this data was used to make marketing decisions Tracking, Targeting or Analysis

7 How does an Service Provider view this merging trend? Bill Nussey, CEO Silverpop

8 Web Analytics: What and Why Web analytics enables marketers to: Attract and convert Web site visitors Increase customer lifetime value Create a multi-channel view of customer behavior New wave of partnerships between ESPs and analytics vendors makes integration much easier than before Even-triggered or lifecycle marketing improves relevance, response and revenues

9 Comparison of metrics by campaign type Campaign Type Primary targeting tactic used Avg. unique open rate Ave. clickthrough rate Avg. conversion rate None, no personalization or segmentation Shopping cart abandon message Product replenishment message Broadcast Triggered Lifecycle Web site clickstream Clickstream Web analytics based targeting 20% 27% 26% 33% 9.5% 9.3% 14% 14% 1.1% 2.3% 2.8% 3.9% JupiterResearch

10 campaigns based on Web site click-stream data can deliver up to 9 times the revenue of broadcast s $500,000 $400,000 $300,000 $200,000 $100,000 $0 $45,600 $5,155 $123,483 $38,191 $222,970 $76,668 $401,942 $162,631 Broadcast Triggered Lifecycle Web-site Clickstream Monthly Revenue Monthly Net Profit JupiterResearch

11 Obtaining relevant customer data First, determine what you need to know Critical information needed to target and segment your audience Web analytics delivers information to boost campaign relevance: A customers interests and preferences Behaviors and events you can observe Stage in the customer lifecycle Products and pricing interest

12 Top Web analytics vendors: Forrester Coremetrics A top tier vendor with deep retail client base Solid technology and emerging suite strategy Omniture All-around solid offerings in product, service and support A safe bet for large enterprises WebSideStory Addresses spectrum of site marketing needs A reporting API that allows build-out of other capabilities WebTrends Flexible deployment model allows for hosted or licensed software Renewed interest from enterprise Web analytics buyers

13 Why are companies integrating web analytics into their core offerings? How does this work tactically?

14 If you re spending 80 percent of your time reporting KPIs and 20 percent on improving them, you need to rethink your resource allocation. Jason Burby, ZAAZ

15 Analytics or Analysis? How are you prepared to manage this process? Jay Kulkarni, CEO Theorem

16 Big Picture Data Sources Process Output Response Site Analytics Individual Pre-Processing Reports & Analysis Offline Loyalty Programs Market Research Ecommerce Lights out Automation Dashboards Algorithms & Models

17 Process Methodology Data Download Merge and Summarize Business Logic Delivery Methods 1 Download data from different sources. Leverage API s 2 Design for scale and automation. Factor in exceptions. 3 Define business problem and crystallize logic 4 Define audience, frequency and format of delivery

18 Key Building Blocks Once tactical data issues are addressed, organizations need to build out more high end solutions. Key items are: Standardizing key metrics for your business. Design phase vs. technical phase. Reports & Analytics Differences? Algorithms and models Business Rules and Decision Trees for your business. Key considerations.

19 Decision Points One size will not fit all when an organization looks to build out operations to merge web & e mail analytics cost effectively. Here are some pointers: Solution may be technology & services combo. What is your core? What skills to keep in house and what to outsource? If you decide to build teams/infrastructure internal, will your economics justify the decision? Customization will be key, by campaign by client. What will it take to get there?

20 Where do organizations start? What are the trend that you are seeing across your clients?

21 Managing data decisions the art of marketing decisions. Margie Chiu, VP Strategy, Avenue A Razorfish

22 Stages of Analytics Evolution Basic Aggregate level tracking of response and site-level conversion. Intermediate Response tagged and tracked by both and site analytics system. Sophisticated Tracking and targeting by site and activity behavior. May also include other tactics such as banners and offline.

23 From Basic to Intermediate Key Activities Tag all links for site analytics system Reconcile vendor and site analytics data Challenges Inconsistencies between data sets (1 st vs. 3 rd party cookie, attribution window) Higher resource demands Data Inconsistency Client found site analytics system counted 2x the orders but 18% less revenue.

24 From Intermediate to Sophisticated Key Activities Passing unique identifier from system into analytics system Segmenting by on-site behavior Challenges Site analytics system s capabilities Low match rate during initial campaigns Higher resource demands Targeted Campaigns Client tested a campaign with no offer by featuring specific products based on site behavior and found revenue per to be 4x to 10x higher than for the general population.

25 Analytics Evolution Checklist Know What You Have: Develop a complete understanding of your vendor and site analytics systems capabilities. Commit Resources: At a minimum, a resource focused on timely basic reports. Ideally, an additional resource with advanced database marketing and statistical analysis skills. Start Testing: Don t wait until all the pieces are in place to get started.

26 What are some good examples of where this worked?

27 Integrated Dashboards David Baker, VP Solutions, Avenue A Razorfish

28 Global Dashboards with KPIs and ROI Media Console KPI Console ROI Index

29 The Campaign Level View

30 Drill downs

31 Domain and Response Models

32 Pivot Table Management Level Dashboard

33 Merging Web Analytics with Marketing to Increase Performance Thank You! For copies of today s presentation,

34 Speaker Contact Information David Baker Jay Kulkarni Bill Nussey Margie Chiu

35 Resources Aberdeen Precision Marketing Benchmark Report Opinions/Aberdeen2006/1120.aspx?CID= e9 WebTrends CMO Smart Report CMOWeb-SmartReport.aspx Web Analytics: Focusing on things that matter Web Analytics: Are your people accountable? 5 Steps to Effective Web Measurement (Omniture) Best Practices for Web Analytics Governance (Omniture) Incorporating Web Analytics into

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