Tribal Fusion Insights Roadshow Oct 2011
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Tribal Fusion Insights Roadshow Oct 2011

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Tribal Fusion's Insights presentation, shown recently in an Australian roadshow to media agencies and trade press.

Tribal Fusion's Insights presentation, shown recently in an Australian roadshow to media agencies and trade press.

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  • Not meant to be an exhaustive list, but most of the players on the previous page are using some combination of the assets described here are building their own analysis on top of it.
  • ANIMATEDThe ratio of impressions to conversions is key. Here we see our four target groups towards the lower right, and our Placid group on the top. [expand]

Tribal Fusion Insights Roadshow Oct 2011 Tribal Fusion Insights Roadshow Oct 2011 Presentation Transcript

  • INSIGHTS SERVICESEXPOSING DATA AND SCIENCE TO HELP PEOPLE MAKE SMARTER DECISIONS
  • AGENDA• WHAT IS INSIGHTS?• HOW WE DO IT AND WHY IT’S BETTER• SOME REAL WORLD EXAMPLES• HOW YOU CAN DO IT, TOO (THE CATHARTIC AND EMPOWERING CRESCENDO).
  • INSIGHTS: EVERYONE SAYS THEY’VE GOT IT COVERED MEDIA OWNERS DATA OWNERS RESEARCH FIRMS RESEARCH FIRMS MEDIA AGENCIES AD EDIA AUDITORS M NETWORKS DSP’S
  • EVERYONE SAYS THEY HAVE LOTS OF GREAT DATAFIGURING OUT WHAT’S GOOD TAKES THREE STEPS.1. What’s the data asset?2. How do they make sense of it?3. How can I use this to plan a campaign? PLANNING ANALYSIS DATA
  • TRIBAL FUSION INSIGHTS SERVICES• Discover the story behind your audience• Learn something you didn’t already know about your customer, and act on it swiftly• Strategic recommendations help you – Improve response rates – Extend your audience – Get more for less
  • EXAMPLE 1: FINDING THE AUDIENCE YOU DIDN’T KNOW YOU HADMARKETING CHALLENGE• A major mobile telecommunications company is tasked with efficient customer acquisition. In a mature market with over 100% penetration, this means stealing customers from competitors, with diminishing returns on marketing efforts.UNDERLYING ASSUMPTION• Mobile is a commoditized offering. The product is not differentiated, so it does not make sense to segment the consumer based on lifestyle, underlying needs, etc.
  • EXAMPLE 1: FINDING THE AUDIENCE YOU DIDN’T KNOW YOU HADTribal Fusion profiled converters and uncovered two distinct personasIMPLICATIONS• Conversions are actually people with full lives.• Speaking to the whole person can improve performance.• Separate creative to these segments leads to higher conversion rates.• Look alike models built off these behaviors extend reach in relevant places.
  • EXAMPLE 2: WEEDING OUT THE CUSTOMERS YOU DIDN’T WANT.MARKETING CHALLENGE• A job site wanted to know why people were visiting their site but not posting resumes.• How can they do a better job of bringing in the right users, and encouraging them to convert?UNDERLYING ASSUMPTION• If no one submits resumes, then employers won’t pay to post jobs. If there are no jobs posted, then no one submits resumes. Left uncorrected, and the whole business could implode.
  • EXAMPLE 2: WEEDING OUT THE CUSTOMERS YOU DIDN’T WANT. TRIBAL FUSION ACTION PLAN • Stop serving ads to people who are clicking but not in the job market. — No more CPA, CPL, or CPC campaigns Site Visits • People looking for specific job profiles are clearly in market, so retarget them until they convert. • Recent grads and moms are dipping in and out of the job market. Hit them with branding campaigns, so you are top of mind when they’re ready. Resumes
  • EXAMPLE 3: DELIVERING CONVERSIONS EVEN WHEN TRADITIONAL SEGMENT/TARGET/POSITION MARKETING FAILS.MARKETING CHALLENGE• A bank was tasked with opening new retirement accounts.• Market research defined the target audience as – Aged 17-64 – Above the poverty line, but not super rich (they have other investment vehicles). – Working or the spouse of someone who isUNDERLYING ASSUMPTION• Targeting basically everyone, so a fancy data strategy won’t help.• Stack ‘em high, sell ‘em cheap
  • EXAMPLE 3: LOOK ALIKE MODELING, BASED ON TRIBAL FUSION DATATRIBAL FUSION ACTION PLAN• TF put a pixel on the conversion page for this product.• Mined the data to see which behaviors indicated lift.• Built a model to de-duplicate.• Served ads to people who had those traits, whether they intuitively “made sense” or not.RESULTS• Look alike model cut the effective CPA in half
  • Beyonce v. Rihanna
  • A SELF-SERVE, WEB-BASED TOOL FOR ADVERTISERS AND AGENCIES• Easy to navigate, intuitive interface• Quickly surface the user behaviors that drive performance• Reduce wastage by targeting the right people with the right message• Extend your audience by defining your own look-alike model