Building a Data-Driven Organization

Many organizations invest in analytics, but only see marginal results. Some companies have pulled back from using analytics for more than basic metrics because it can be costly to pursue, while others have embraced analytics and are thriving. This is one of the key points made in Thomas Davenport's paper "Competing on Analytics" (note: Harvard Business Review charges a fee to access the paper).

We live in a time where information spans the globe in seconds. This creates an environment where it's hard to differentiate one's products in a highly sustainable way. Even if you get a temporary edge with your product(s) through some innovation, it won't be long before your competitors know what you did, how you did it, and how to replicate it.

However, organizations can make a difference with their operational processes and their methods for decision-making. Organizations with streamlined operations, plus fast and accurate decision-making, can gain a decisive edge.

One important step for an organization to take is to become data-driven. This requires a few key things:

  1. Having a voracious appetite.
  2. Putting in place the systems and technology to collect the data on an ongoing basis.
  3. Hiring the people who can decide what metrics are important, gathering the data, and then analyzing it.
  4. Being prepared to act on what you learn, even if it means changes in organizational policies or structure.

All of these are great things to put in place, but they work best when analytics emerges from a centralized structure driven by the top of the organization (the CEO).

Make It Meaningful (and Actionable)

One problem organizations encounter when using analytics is figuring out what to focus on. For example, in the world of Web analytics, there's so much data available that you can get completely lost in it.

Don't spend time cruising through your analytics software exploring one interesting fact after another for no purpose. Work on things that are important to the business from the beginning. Think about this before you even put your analytics systems in place.

Also, recognize that what you want to focus on will change over time. Analytics is a learning process. Experience using the tools, and thinking about how to use them, will inevitable result in changes in thinking. Of course, the actions of your competitors can have that affect, too.

The key takeaway here: go after big things that will have a real impact on the business. Chasing data that may save you $1.25 a week doesn't qualify. You organization likely has limited resources for executing, so you should focus them on things that bring big returns (such as lowering the cost of your PPC campaigns by 20 percent while maintaining the resulting sales).

Also, be sure that the things you're working on are actionable. Finding out that you can save money on operations by moving your business to the Malagasy Republic may not be helpful, for example.

Be Multi-Dimensional

If your organization works across many channels, then look at the bigger picture. This includes online-only businesses that use organic search, paid search, contextual advertising, and display advertising.

This gets harder when you have brick-and-mortar stores. The types of data you can collect are very different, as are the systems for collecting the data. You may rely on surveys, membership programs, and store-by-store data. Online-only or online and offline, the effort to look at the data across systems is well worth it.

Even in the PPC world, there are times when this comes into play. One of the simplest examples is that branded search terms always offer the highest ROI. People who search on brand terms have left the research and discovery phases of their buying process and are ready to act.

In combination with that, the paid search campaign may have many keywords which don't appear to be performing that well, because most analytics systems credit 100 percent of a sale to the last keyword receiving a click.

An increasing number of people who buy online do multiple searches before buying. They may come to your site on a generic term, such as "digital cameras," but only make the purchase at a later time after searching on a very specific term, such as "Canon PowerShot A590 IS."

Your evaluation of the performance of the term "digital cameras" in your PPC campaign may show that it's losing money. So you may lower the bid, but end up lowering your profits at the same time. Why? Because the search on Canon PowerShot A590 IS would never have taken place if the search on digital cameras had not taken place first. If you weren't there on the term digital cameras you wouldn't have gotten the sale.

This gets far more complex when you start crossing channels. Perhaps your first click occurs on a display ad, or someone comes to your site because of a TV ad you ran. As you can see, it can get quite complicated.

Analytics is a Differentiator

Perhaps one of the lessons here is that a comprehensive analytics strategy may be tough to put into place. But putting it in place can result in huge gains for your business. It can help you streamline your operations, make you more responsive to the market, and increase the speed and accuracy of your decision making.

Join us for a Search Engine Marketing Training in Boston, November 6 at the Hilton Boston Back Bay. Not only will you walk away with the knowledge and skills to be a successful search engine marketer, you'll also jumpstart your career and enhance your professional know-how.