Filed under: A/B Testing, Actionable Insights, Business Intelligence, Data, Datarati, Testing | Tags: A/B Tesing, Conversion Funnel, Multivariate Testing
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With many new options in the marketplace for purchasing display media, advertisers are taking a hard look at the value of each “link” in the traditional advertising value chain, from agencies to networks to data providers.
The links in the purchase funnel (display ads, search, etc.), however, still manage to escape similar scrutiny.
Imagine if you rewarded your ad server with the bulk of your media budget, simply because they are closest to the ad’s final placement. Last-click attribution essentially takes the same approach. While reluctantly accepted for its simplicity, the model’s strengths end there.
Currently, a substantial number of our advertisers are applying a last-click attribution model for their campaigns.
Advertisers are well aware of its shortcomings, which have fueled the debate about display attribution models for years.
Recognising these challenges, DataXu’s Advanced Analytics Group frequently works with customers to analyse their unique attribution data and develop customised strategies for their display campaigns.
Taking a look at this data for six campaigns, the team identified some interesting trends.
Data Insights & Trends
– For all campaigns, last click attribution ignored 97% of spend driving conversions — which often results in over-spending in search and re-targeting, and under-spending in display that drives demand creation.
– The recommended attribution period for short consideration products, such as CPG, is two weeks. In the campaign shown above, this window includes 90% of impressions that converted.
– The recommended attribution period for long consideration products, such as Insurance and Autos is five weeks.
– The length of time it takes to attribute 90% of conversions varies by 250%; each product requires its own distinct attribution model.
Ultimately, no two campaigns are alike, and what drives their success is tough to predict at the outset, but incredibly valuable to understand.
GoodData is rapidly becoming a key example of the technology innovation emerging from Central Europe – and laying a bet on Europe seems to be paying off forFidelity Growth Partners Europe, the venture and growth equity investor, which backs European entrepreneurs exclusively.
It’s invested $2 million in the startup, the second investment for the £100 million fund, leading an overall $6.5 million investment round.
Filed under: #mktgcloud, Datarati, Marketing Automation, Marketing Cloud | Tags: Pitney Bowes, Portrait Software
Pitney Bowes, a provider of software, hardware, and services, recently acquired United Kingdom–based software applications provider Portrait Software. After assessing the supply chain management and enterprise resource planning (ERP) space, Pitney Bowes executives felt they needed to beef up the company’s business process and rules engine capabilities.
The executives also sought to acquire bi-directional marketing automation and an analytics workbench. “What we saw in Portrait,” says Kyle Kittleson, director of corporate strategy and M&A at Pitney Bowes Business Insight, “was that [those] technologies were orchestrating in the service of optimizing customer interactions and customer lifecycle.”
Local deal goliath Groupon is launching a major new feature today: deal personalization, giving the site the ability to send you the deals it thinks you’ll be most interested in.
Before now, Groupon has always offered one or two deals per city per day to its users.
That’s still going to be true, but with a twist: the site will be sending different deals to users based on criteria like their gender, buying history, and their interests.
The change may sound fairly minor, but it will likely have a big impact on Groupon’s bottom line.
A great infographic from the guys at @flowingdata
Last month Twitter announced the acquisition of Smallthought Systems, an analytics startup that helped the microblogging site create its online internal network based off of DabbleDB. Terms of the deal were not disclosed.
While Twitter had worked with Smallthought on the Dabble project, the startup caught Twitter’s eye with the creation of Trendly, an tool that helps web sites distinguish signal from noise in their Google Analytics data. Twitter started using the service and realized that it would make an complimentary addition to their analytics team in terms of both talent, and technology.
Analytics are a part of Twitter’s monetization plan, as the post indicates that the analytics team will be focusing “on integrating ideas from Trendly into our current tools and building innovative realtime products for our future commercial partners.” Clearly Smallthought will help boost any in-depth analytics offerings Twitter may have up its sleeve.