It’s great these days, isn’t it? When it comes to measuring and analyzing the performance of your digital channels, there’s an abundance of free or cheap tools that you can use across the spectrum of different measurement technologies. At the last eMetrics conference I went to, there was a session devoted entirely to the best free tools there are out there, whether they be web analytics tracking tools, surveys tools, competitive analysis tools, social media tools, or site performance tools. You don’t have to be a large, sophisticated online marketing organization to be able to collect lots of data cheaply. Unlike other marketing channels, the marginal cost of data is very low.
So all this free or cheap data must be a good thing, right? And the return on investment (ROI) must be really good since you don’t have to spend a massive amount on getting the data. Right? Well, I think it all depends on what you do spend your money on and what investments are actually made. Here’s a scenario we see a lot with the daddy of free tools, Google Analytics.
An organization has a website (or possibly multiple websites). It decides that it needs to do some tracking to see what’s happening but doesn’t want to spend too much money at this stage, and so decides to use Google Analytics. This is fine; Google Analytics is a strong, robust web analytics tool with a user-friendly reporting interface. Next, a developer puts the tag code on the site, data begins to flow, and after a while pretty charts begin to appear. At this point, things look good, data is coming in, and not a lot of effort or cost has been expended.
Next, the organization starts to try and use the data. Some of it seems OK but other bits may not look right. People start asking questions, but it proves difficult to get the answers from the data that’s in the reports. After a while, people begin to question the value or even the integrity of the data. So while not much has been expended, not much has been gained either, so the ROI is not very good. The organization may struggle on for a bit trying to get better data or reports, but ultimately remains frustrated. At this stage, the organization may look for help. One option would be to invest in developing or hiring a skilled resource within the organization and to dedicate someone (or part of someone) to looking at the data and creating some insight from it. Other options include using a consulting organization, and often this is where we get involved.
A typical approach would be to understand what the business is trying to do and therefore what it needs to know. By understanding what the organization needs to know, it’s possible to work out what data needs to be collected, and once that’s done, it’s possible to figure out how the code on the site needs to be configured to ensure the right data is collected in the right way. The reporting interface can then be configured so that people get access to the right kind of reports they need rather than a “one size fits all” approach to reporting. Often we’ve seen that relatively modest levels of investment in either people or professional services start to dramatically increase the integrity, utility, and value of the data that the organization is collecting and reporting. The ROI starts to improve as decisions are made on the data that improves business performance or reduces risk.
I’ve used Google Analytics as an example here as it’s a widely used tool in the digital space, but the arguments apply to the many cheap or free tools out there. Free or cheap data isn’t necessarily good data until someone starts to add some value to it, and organizations are unlikely to see any return until some investment is made in ensuring that the data is relevant to the needs of the business and fit for its purpose. Don’t get me wrong, I’m all for cheap data, but don’t fall into the trap of thinking that juts because it’s free that there isn’t going to be any cost of ownership.
This column was originally published on August 30, 2011 on ClickZ.
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?
One of the major challenges in the martech industry is getting the attention of prospects in a world where they are bombarded by content and emails on all sides.
Facebook is addressing one of the biggest missing pieces of its chatbot offering: analytics.