The Heart of Analytic Success: SMART Goals and the Trinity Strategy

BinaryHorizonatal

For our first analytics class, Sofia provided an overview of what analytics is, its value and how every successful project must start with SMART goals. Sofia defined analytics as the use of data to gain insights and make better decisions. I agree with this but would add that analytics helps you report up to decision-makers on how investment in your initiative has impacted behaviour and user experience to advance business goals, as reflected in outcomes. Analytics also helps you gain executive (or client) buy-in for future projects that build on a prior campaign’s analytics or results.

I think analytics is becoming increasingly important as we continuously have more volume and variety of information or ‘big data.’ Sofia defined big data as “a collection of data from traditional and digital sources inside and outside a company,” which companies are increasingly looking at for ongoing discovery and analysis to inform their decisions. This data includes many things we can measure and analyze from digital sources, such as how many people access a website through specific social media platforms and from what countries, as well as traditional sources, such as how much money an event raises or how many people attend it. What I found particularly new was learning the difference between ‘structured’ data, which is quantitative, such as how many visitors access your site via Twitter, and ‘unstructured’ data, which is more qualitative, such as comments posted on your company’s facebook page.

Before you can attain analytics, you need to set goals for a website or digital property. Sofia explained that you summarize each goal in a sentence that includes Specific, Measurable, Attainable, Realistic and Time-bound (SMART) attributes. This is a slight variation from PR campaigns (which I’m familiar with), where goals are broad and objectives have SMART attributes. In PR, I’m also more used to setting goals and objectives for campaigns with a definitive end point.  In this first class, we did an exercise to identify a website’s goals. The feedback from this exercise gave me the impression that SMART goals can be for an overall website or company (such as the Toronto Star) versus a set campaign. If that’s the case: how can you make these goals time-bound?  I think you might set them for an initial period goal, such as six or three months, and then reassess but it would be good to know for certain.

Sofia told us the grandfather of analytics is Avinash Kaushik, who discusses his theories extensively in his blog: Occam’s Razor.  The blog is named after a 14th-century English logician and one of the alternate translations of his principle is: plurality should not be posited without necessity.  I think this suits analytics because it provides a methodology for specifically identifying what big data an organization needs to measure and why (necessity), versus trying to measure all the data it can access (plurality).

We also learned about Kaushik’s Trinity Strategy. This is a strategic approach to extract insights and metrics from a website/other platform, based on the users’ behaviour and experience, as well as the overall outcomes.  It’s imperative that these insights and metrics can be ‘acted on,’ that is used to make decisions that alter the organization’s approach or to design future initiatives.

For example, let’s say you implement a promotional campaign to sell featured books highlighted on a page in your ecommerce site. You also promote it through direct mail flyers and social media. Your goal may be to sell 50 copies of each featured book within one month. The overall process begins with the clickstream data, which is the data collected through the site. I can include: who is accessing the book page, from where, via what devices or user path, etc. From this data, you can measure and assess users’ behaviour in response to the promotion, such as:

  • How many came to the site via each social media platform?
  • How many were driven there by the flyer?
  • Which book image or caption attracted users when they first landed on the page or made no impact for the duration (as measured by a heat map)

You then measure outcomes, such how much revenue was generated through specific online book sales. The third element is the experience, which tells why the users behaved the way they did. My understanding is this data is often accessed through additional steps, such user testing to measure effectiveness of user paths, experimenting  with site changes (e.g. trying book purchasing buttons in different positions) and customer/user surveys to assess how they feel about the site. These three elements, combined with competitive intelligence, help you uncover insights about what is attracting users to the site and getting them to buy the books, as well as what changes might improve outcomes. For example, in assessing this data, you may want to adjust the page layout, if users consistently miss a specific book displayed.

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