Do you think about data you’d like to ‘track’ in [your technology system of choice]?
It’s easy to be sucked into the mindset that simply gathering a new collection of data points can be transformative. The concept of a consolidated, holistic look at customer data is touted as a meaningful business advantage and part of the value proposition of most CRMs. It’s also baked into the product names and marketing language: Salesforce Customer 360 or Microsoft Dynamics 365 Customer Insights.
In order to realize these gains, it’s critical to understand and prepare for the complete journey so you don’t end up stuck at an intermediate step with most of the costs and few of the benefits. Start with the business questions you want to answer and the changes that you’ll make when you have the answer to those questions—don’t prioritize capturing data until there’s an actionable strategy behind it.
Be clear about what you’re trying to accomplish
Humans are pretty good at asking broad questions like “what should I do to increase revenue this year?” Computers are (for now) pretty bad at answering this kind of question. In order to get meaningful information, you’ll need to reframe the big human-sized question into something more specific like: “what marketing assets were the most effective at engaging people who [donated/purchased]?” It takes a general goal (increased revenue) and narrows it down to something much more specific (understanding common points of engagement for converted customers/donors).
One way to tease out assumptions and expectations for data collection is to actually draw out the report you imagine with hypothetical numbers. A visual can help align a team around a shared understanding of the outcome, and proactively raise questions like how to categorize or aggregate the data. These decisions can then inform (with the end result in mind) how to structure the data collection on the front end.
Finding a place for your data isn’t the only hurdle
The technical challenge of storing data in a way that can provide a desired metric is only part of the challenge. Additional factors to consider before you start dumping new data into a CRM include:
1. Cost of storage
The best way to think about this is a small but non-negligible tax on every human interaction with a piece of data. Time to enter it manually, configure and maintain integrations, document fields and usage, or figure out how to make changes in the future. This tax is real and can add up. Gigabytes are cheap but the mental capacity to figure out what goes where isn’t.
2. Data quality
Data can flow into a system in a variety of ways, and each path has its own considerations that can negatively impact quality or completeness of the data. From fringe cases that weren’t considered to integration errors to user frustration and shadow systems, clean and complete data collection isn’t a given.
3. Use in decision making
Is there a clear analytics plan for surfacing information to stakeholders, and do those stakeholders trust the data enough to make decisions based on it? Clear, well-constructed reports and dashboards are the first step, but it’s also critical to have a decision-making culture that recognizes the value of data and incorporates it into the process with an open mind. The fanciest dashboard in the world isn’t providing value if nobody looks at it or uses it to question their own assumptions.
4. Implementing changes
Much of the time, correcting course based on insight gained from data will require some initiative and/or level of change. The change might be tactical or strategic, but without the capacity to pivot and adapt, the magic of leveraging your data can’t be fully realized. Eight personalized marketing segments sounds great until you realize that nobody has the capacity to regularly craft different messaging for each group.
A data collection value checklist
Next time you start to contemplate collecting a new category of data with aspirational thoughts about the transformative business value it will provide, ask yourself the following questions:
- What’s the question I’m trying to answer and why is it important?
- If I had the answer in front of me, today, what happens next?
- Do we have the capacity and alignment to execute on that vision?
- What’s it going to take to maintain high-quality data we can rely on?
- Is the effort to do so likely to yield a high ROI?
Ticking off each question with a clear answer is a good indicator that you’re set up for success. If you struggle to come up with an answer, it might be a good idea to think a bit more critically about that particular question before you jump ahead to adding more data to your system.
