This classic exchange from a December 1994 episode of Seinfeld sums up the state of today’s analytics tools.
Agent: I’m sorry, we have no mid-size available at the moment.
Jerry: I don’t understand, I made a reservation, do you have my reservation?
Agent: Yes, we do, unfortunately we ran out of cars.
Jerry: But the reservation keeps the car here. That’s why you have the reservation.
Agent: I know why we have reservations.
Jerry: I don’t think you do. If you did, I’d have a car. See, you know how to take the reservation, you just don’t know how to *hold* the reservation and that’s really the most important part of the reservation, the holding. Anybody can just take them.
Analytics tools have come a long way in the last few years. Thanks, in large part, to an explosion of SaaS platforms and cloud based deployments, new tools and services that make it easier for companies to collect, analyze, and display data are popping up every week. Unfortunately, I am seeing too many companies that end their analytics project at the visualization stage, when they need to be using data to drive their business goals and KPI’s. In Seinfeld terminology – They know how to collect their data they just don’t know how to act on their data.
Nowhere is this more apparent than in the world of online advertising. As Product Manager at Viewbix I pour over customer analytics every day. I look for trends that can help us improve our product by identifying what features are working and what are distractions. A large part of my time is spent talking to customers to try and understand what the goals of their campaigns are. What surprises me is how often customers ignore the data that they themselves have in hand. It frustrates me when I point out to a customer that an ad running over channel A is producing 2X CTR over channel B and yet currently 70% of traffic is pointing to B. Why did they not pick up on this themselves? Why are companies not using their data? Or, as Jerry might say, “That’s why you have the data!” Companies today think they “Know why we have the data!” but are either lacking the proper tools to leverage their data or are ignoring it because that’s not the way they’ve used analytics in the past, i.e. why rock the boat. (more about this in an upcoming post).
The root of the problem is that companies are using an outdated data pipeline model that starts with a collector and ends at visualization. Doing a quick Google search for “typical analytics pipeline” will turn up hundreds of variations that basically look like this:
Missing from this model is an Action layer.
To counter this Viewbix has a patented “Vsense” engine. Vsense™ can use data to determine in real time what creative changes will produce the best result based on the customer viewing the ad unit. If a user viewing an ad has been determined, based on our data, to match a profile of a user who will share an ad we can in real time decide to show social sharing buttons based on this data. If not, don’t bother showing the button as it distracts from the goal of the campaign. Vsense™ uses huge amounts of data to automate decision making.
There are signs that the industry is moving in the right direction and other companies are introducing their own flavors of what we call “Actionable Analytics”. Next generation analytics tools are beginning to extend the data pipeline past visualizations and allowing businesses to set up real time rules based actions that trigger and respond to events even before a user has time to analyze.
Google recently packaged together a suite of tools under the name Analytics Suite 360. Instead of a disparate set of marketing tools that don’t communicate with one another, customers can leverage the integrated suite pf products to gain a holistic view of their marketing efforts and begin to connect actions and data. Unfortunately, Analytics 360 is targeted to large corporations willing\able to put down 150K for a basic setup, and to reap the benefits they must be “all in” on the Google platform.
Another approach is that of Snowplow Analytics. Just a few weeks ago Snowplow introduced its open source Sauna product. Sauna, billed as a “decisioning and response framework” allows customers to tap into their analytics engine and perform automated actions based on data gathered. An example would be creating a new Mailchimp segment when a certain number of users are collected with a matching profile. The product is still young and only supports a small number of integrations (Optimizley and Sendgrid) but promises many others down the road.
Both Snowplow and Sauna require highly technical integrations and are aimed at companies with an internal IT staff who can put all the pieces together or at those who will use it’s Managed Services to implement and maintain the pipeline.
Like Viewbix, both Google and Snowplow are tackling a major problem with today’s analytics tools. They are both realizing that the current data pipeline model is broken and are extending it past the visualization\presentation stage by adding a layer of Actionable Analytics …And that’s really the most important part!