10 Gotchas to Avoid When Updating Your Analytics Strategy




PHOTO:
Pawel Janiak

Developing strategy keeps CMOs awake at night. Add in the complexity and uncertainty the COVID-19 pandemic produced, and you can’t help but wonder if CMOs will ever get a good night’s sleep.

Some of the industry uncertainty comes from the revised timeline Google announced around its cookie ban. Even the question of whether business teams can work remotely versus reporting to the office creates potential issues around data reporting workflows.

Despite these factors, it’s an excellent time for marketers to make adjustments to their analytics measurement. Although it’s August, the holiday season is just around the corner, and it’s likely your competition is in the same jam as you. By adjusting your analytics now, you won’t miss a step with campaign timing.

Before you jump into an analytics refresh, here are a few gotchas to know. Avoiding these can help establish the right workflow to conducting effective analysis, even in these turbulent times. 

1. Asking Overly Broad Analytics Questions

Going into analytics asking general questions will lead to answers without a clear call to action. Marketers should ask focused questions around the business problem you want the analytics in the site and app to solve. You can then plan specific analytics reports, tags and tools accordingly. 

For example, asking binary questions such as “Are people viewing my white paper landing page?” will only result in “yes” or “no” responses. Instead, you should ask what online sources are consistently bringing customers to your page. Is there an audience opportunity within the data? Selecting questions will help you plan the right metrics and identify the best reporting structure.

2. Not Establishing a Clear Timeline for Analysis Development

You need a timeline for short-term analysis and for long-term. The short-term ties to campaign needs, but long-term should focus on developing advanced models and supporting connections to data. Clarifying a timeline encourages an evaluation of where resources are best deployed.

Related Article: What 2020 Analytics Trends Will Remain Trendy in 2021?

3. Testing Everything the Customer Sees Online

Having a clear timeline simplifies the creation of an A/B test schedule. Managers may be tempted to test every element of a user interface, but this is impractical from a resource and cost standpoint. Strategic testing can direct focus on the elements that truly influence the customer experience, helping you reach more meaningful conclusions.

4. Onboarding New Martech Solutions too Soon

Sometimes adding tools with unclear expectations of how the technology will solve data problems creates technical debt. People may, as a result, stop using the tool because of the uncertainty of its role in a workflow. The current debates on whether professionals work in an office versus remote can exacerbate the problem further because remote work can obscure potential data workflow concerns when they are not discussed daily. Tools like Microsoft Azure Purview, which I cover here, are becoming essential to managing data across a martech stack and the associated data sources. Get clear consensus on the pros and cons of current tools before seeking a new solution.

5. Spending too Much Time on Quick Hits  

Questions such as “How many visitors do we have?” are fine for a website or media launch. But as campaigns move forward, investing too much reporting time exploring those quick hits shortchanges the time and discussions spent on advanced analysis. An example of this is determining if a cohort of customers exist among social media traffic results. Identifying a cohort and determining its value to a business takes more effort than reporting visits and session metrics. Allocate the time to pursue insights, or ask the team what time is needed for deeper analysis.

Related Article: 7 Factors That Determine Email Deliverability

6. No Relevancy to Day-to-Day Activity

At times, analytics will need to explore areas outside a production environment, such as testing an API for its data quality or refining a SQL query. But getting caught up in isolated analysis which don’t relate to the business objective will result in time wasted on pointless optimization tasks. Always ask why interest in a given data or metric is needed.

7. Overlooking Considerations of Sales and Marketing Teams

An analysis, be it as continuous reporting or ad-hoc, should tie to Marketing Qualified Leads, Sales Qualified Leads, or both. Doing so means talking to marketing and sales teams about what is working in the customer journey and what is not. The pandemic has accelerated trends involving the customer journey, so checking in, even as a virtual informal discussion, can lead to new ideas.

8. Getting Outside Help too Late

Consultants bring familiarity with the latest martech as well as experience within your industry. They will share their knowledge through unique, timely suggestions to help shape your decisions related to marketing media or data sources. In short, look for experience to help your team save time in determining how to use data and solutions efficiently.

9. Not Discussing Data Governance With Vendors

Governance keeps everyone awake at night, not just CMOs. But it’s possible to reduce some of that worry by reviewing vendor data policies. Get a sense of how data compliance is managed among your team and partners. This is especially useful against new legislation, such as Colorado’s new privacy law. Discussions with vendors open the door for APIs audits to make sure the data being used in your organization reaches compliance.

Related Article: What Marketers Need to Know About the Colorado Privacy Act

10. Viewing Bad Analytics News as Irredeemably Bad

Communicating bad news is part of reviewing data and reporting systems. In all honesty the news is not really bad — data reveals trends that need a systematic response that requires time to develop. Analysts must be the storytellers of data. Tell what happened through the dimensions and metrics reported, and then tell the consequence or potential consequences for objectives. Ultimately management may just need analysts to tell them what tradeoffs they’re facing before deciding how to improve the situation. Use that perspective to give an overview.

Follow these tips … and share yours as well. What opportunities do you see to adjust analytics during the dog days of summer?

Pierre DeBois is the founder of Zimana, a small business digital analytics consultancy. He reviews data from web analytics and social media dashboard solutions, then provides recommendations and web development action that improves marketing strategy and business profitability.





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