Many analysts view data with the same expectations, regardless of where it comes from (reminding me of Marshall McLuhan’s dictum that “the medium is the message” -- the way we acquire data has a lot to do with what we can do with it) -- and end up coming up short.
Worse yet, the isolated analytics readouts (unnamed because they are legion) provide misleading information that result in the wrong conclusions when followed too literally. Most analytics platforms report on metrics by silo because this is much easier for the data vendor to build (for example, Twitter followers, visitor bounce rate, Facebook Fans, and so on), and the readouts fail to lead to any meaningful action. What's needed is the ability to categorize data, using taxonomies, as it comes to your business system. But attempts at merging customer relationship management, social media data, and search data with Web analytics outputs are usually fruitless tasks for today’s set of platform tools, including data warehouses.
Gary Angel, president and CTO of Semphonic, a digital measurement and data analytics consulting firm, addresses this 360-degree data gap in a recent white paper for Anametrix, a digital analytics firm. Angel argues that instead of isolated channel readouts, businesses need a complete map (building a model of how a business or enterprise is fed by all its interactions with customers and clients) and an understanding of the pathing customers take to reach their goals. You can think of this in terms of an analytics engine: Each cylinder needs to fire properly, with the data silos being the cylinders that work together to move the engine (and entire car/enterprise) forward.
Such an analytics engine should feature three capabilities. Unfortunately, these are difficult to find in any single platform, whether for small or large businesses, available today.
- Segmentation of interesting sources of traffic. For example, the tool would be able to show not only that bounce rate is high on your restaurant chain's home page but also which customer types are experiencing the high bounce rate and what their goal for being on the Website is in the first place.
- Multichannel integration of data streams into a model of how the whole system works. This means having an understanding and visual mapping of the end-to-end customer experience with the business and the ability to see how changes in one area or channel affect everything else in the system.
- Intelligent dashboard reporting that can roll up the data stream information acquired into silo- and site-wide key performance indicators for use analysis by key stakeholders and executives. The language of the dashboard front end should match the language and vocabulary of the business (such customization is a particularly rare feature).
Naturally, the white paper discusses the Anametrix solution, which comprises a next-generation data visualization engine coupled with a data model that organizations can use to build their “data engine” maps.
The point is most Web analytics and social media analytics toolsets provide neither the full segmentation needed for an effective model-based system nor any or enough visitor-based information (for a variety of reasons related to privacy and expense of housing this data), and this makes it hard to overlay the data/metrics being collected with other disparate house and third-party information. Nor is it possible to apply the more intense big-data calculations that are becoming more and more necessary.
But once you can look at the activities and return of investment of an entire model of your business data, making fully informed decisions based on it is much easier and more accurate. Such decisions will grow the business to be profitable and rewarding -- not only for itself but also for its customers. Wouldn't you agree?