Evolve Into a Data-Driven Organization, Part 1

When Forrester Research asked Web analytics users what the hardest part about using analytics is, 53 percent said acting on the findings, more than double the 24 percent who said it’s pulling data together. Until organizations actually act on data, a Web analytics initiative’s return on investment (ROI) is zero. Acting on the data is the most important element of Web analytics — and the part organizations struggle with the most.

When you transform from a company operating on instinct to one operating on data, a number of roadblocks can arise and potentially derail your efforts. Having helped a number of clients make this transition, I’ve identified the most common stumbling blocks, and some solutions that help organizations overcome them.

Lack of Methodology

If you don’t have an established process or methodology for utilizing data to identify problems, recommend solutions, and roll out improved content, success is difficult. You must adopt a process that helps identify and prioritize opportunities, as well as act on the maximum number of opportunities that will yield the most significant results.

Your process must also include a method to evaluate the success of changes made to the site. To be successful, make sure you get agreement from all parties involved. Here’s the cyclical optimization methodology we use:

ZAAZ Web Analytics Methodology

No Proper KPIs or Metrics

As the first step in the analytics methodology indicates, setting proper key performance indicators (KPIs) and metrics that are tied to overall business and site goals is the foundation of all successful analytics initiatives. Without well-defined, prioritized metrics, you can’t truly maximize Web analytics’ ROI.

Set the foundation of your most important metrics as a Web team so everyone involved focuses on the same top-level performance metrics. We’ve found starting at the highest level and working down to specifics is the best way to approach this process:

  1. Review corporate goals.

  2. Define the Web channel’s role.
  3. Define the desired Web behaviors.
  4. Assign KPIs to most the important behaviors.
  5. Make sure all parties support and believe in the priority given to each KPI.

Data Overload

As an organization collects different data types to make decisions, data overload can very quickly become an issue. Often, in an attempt to “see the entire picture” by pulling in all available data, the organization buries the truly valuable, actionable nuggets among the rocks. It’s nearly impossible to dig out those nuggets unless you’ve clearly defined the KPIs and metrics.

To overcome data overload, focus on the most important KPIs. Pick the most important site conversion or behavior that best drives the overall business, such as a lead generation form, signup process, or e-commerce funnel. Concentrate your efforts on fully understanding that process and ways to optimize it.

Potential Site Changes Aren’t Monetized

If you can’t monetize the site changes’ outcome, you’ll find it difficult to compare different types of changes across your site or business. If there’s no way to tie any benefit back to the business, you may want to focus resources on something that would have a greater effect on the business.

Estimate the potential changes’ effect and assign a dollar value to it. You won’t know the exact outcome of proposed changes before you make them, but estimating a range of potential effects to estimate the outcome is important. You can monetize potential changes based on:

  • Increased revenue

  • Increased profitability
  • ROI on campaigns
  • Increased lifetime value
  • Reduced customer service costs
  • Increased leads (based on a lead’s value)

Opportunities Aren’t Prioritized by Potential Outcome

Too frequently, site changes are based on what was first scheduled or goals for updates made at the beginning of the year or quarter. They should instead be based on their potential effect on the overall business.

After monetizing potential changes, you can better compare all opportunities against each other. Don’t be afraid to juggle initiatives based on the biggest outcome. Don’t automatically put new findings at the end of the list of initiatives, especially if they have the potential to make a significant improvement.

Once monetized, use that information to determine the cost of waiting six months to roll out the changes. This often requires a change in the way things are prioritized and when changes are pushed out to the site.

In part two: five more roadblocks in evolving into a data-driven company.

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