When it comes to digital analytics, it’s all about asking the right questions. You have to demonstrate a thorough and complex understanding of the story behind the data. It’s become common practice to review numbers and carry on without questioning them. Sure, it can be helpful, and arguably admirable, to have extensive knowledge of a tool’s interface, but there’s something that’s significantly more crucial.
Data analysis fails when there’s an inability to think critically and ask questions that dissect the information at hand. This is such a paramount phase of the process because it’s much more difficult to drive meaningful results and accomplish business objectives without it.
You may be thinking, “I still don’t understand why asking business questions is relevant here.” Well my friend, let me tell you.
Avinash Kaushik explains why this is important by taking a look at the various challenges that businesses face. As it turns out, these obstacles can be unexpected, surprising even. And while many think it’s a best practice to apply a formula or algorithm to find the solution, the truth is, the result isn’t as insightful as it appears. This isn’t always the best intuitive way out. Kaushik makes a compelling point by sharing that unique brands aren’t the target for standard analytics tools. If you’re going to position yourself as a leader in the industry, your internal practices have to be just as exceptional to parallel with your brand identity. So, what questions can you ask to reform the way you’re understanding data and analytics?
1. Does that data meet the standard for being accurate and trustworthy?
If the data you have isn’t reliable enough to be deemed accurate or trustworthy, I hate to tell you, but it’s absolutely useless. Coordinating an analytics audit is key to evaluating the quality of the data. Examine whether or not your Google Analytics data is sampled because this will tell you a lot about how you’re reading the data. Google Analytics will allow you to run a full exploratory, known as a health check. This requires users to review each report under their account to determine how the data reads. Experts say it’s more than likely your business has some issues, like pageview tracking or erroneous event tracking, but these are things that can easily be ironed out once the problem has been detected. While the health check practice isn’t common, businesses that take the time to invest in all it has to offer learn so much in just one check. It also helps businesses to get in a routine of identifying quirks to ensure long-term data integrity.
2. Does the data align with the output provided from other systems?
Because data can be interpreted from numerous angles, it’s crucial to assess whether or not the data sources align with one another. It’s not abnormal for Google Analytics eCommerce data to have minor differences from data cultivated by eCommerce software, but it should be approximately 95% the same. For this reason, analytics experts recommend integrating testing tools with analytics data so businesses can easily determine if the results are skewed, and if so, by how much.
3. Is the data telling the whole story? Are there crucial pieces that aren’t being represented here?
You’ll want to challenge your perspective enough to ask the types of questions that identify weak spots in your data. Some questions to consider:
- Have you properly set up the default URL?
- Have the referral exclusion settings been configured the right way?
- Have you enabled the enhanced link attribution?
- Are your demographics and interest reports functioning as intended?
- Are all offer Google Webmaster Tools turned on and connected to the correct links?
- Is AdWords Integration accurately configured? Can you view the PPC data? Does the system correctly record clicks and sessions?
It’s important to note that cross-domain and subdomain tracking can present a common problem in the digital analytics realm, so be sure to check this out.
4. How can you optimize measurement tactics to inspire more meaningful results?
If you’re going to take the time to closely review the data, it’s common sense to do so with the mindset of maximizing your results. This thinking replaces “Can I trust these numbers?” and “Does this mean what I think it means?” with questions that elicit deeper thinking, like “How can I leverage tracking options to generate optimal insights and actionability?” and “How can we position this data to be intuitive, usable and easy to understand by the teams that will put it into action?” Other questions you should ask include:
- What upcoming events can you use to track customer behavior? What events are significant enough that you can buy into the hype and drive results for your brand?
- Have you determined specific outcomes, conversion points, KPIs and dashboards to guide your success?
- Is it beneficial to consider using segmentation, merchandising or campaign optimization?
- Are you using behavior targeting? If so, can you implement behavioral personas to guide your targeting efforts?
- Can you filter through data or merge existing sources to piece together different elements of the customer’s journey?
Above all else, remember that the data you acquire only has the potential to help you if you choose to be actionable about what it’s telling you. Consider ways you can determine what you’re missing and be intentional about integrating meaningful solutions that translate as impactful results.