THE RISKS OF BEING TOO DATA-DRIVEN*

In business today, data is everything. And proudly proclaiming that your organization is “data-driven” is not just a given, it’s a mandate. Firstly, data helps inform the decisions you make leading to your strategy development and gives substance to the abstraction of it. And metrics provide direction for strategy activation, helping you continuously improve and optimize your execution.

But what if I told you that you could be too data-driven?

Because there are real risks with being overly data-driven, and its by-products can be harmful for your marketing, and your business.

Data can be unclean or, worse, misleading or meaningless: Unfortunately, companies don’t spend a lot of time cleansing – or corroborating – their data. But data can be filled with errors or holes. Spending time and resources on bad data is not just a waste of time but a danger to your strategy and brand.

We’ve all worked on insights from a campaign and then found issues with tagging and data collection. Activating on bad data obviously won’t produce the results you’re looking for.

And many “data-driven” organizations are in reality focused on meaningless or vanity data –with no real connection to or indicative of in-market success. I once worked on a lead generation campaign to launch of a new car that set a goal of 100,000 leads. We then tracked and optimized relentlessly against cost-per-lead – a meaningless metric, as it turned out. While the campaign was successful in hitting the lead goal, we found that a huge percentage of leads were low quality.

Implication: Confirm the value of your data by checking both the validity and the relevance of each metric/KPI

Analysis-paralysis: The best organizations use data as a tool – helping both to guide strategic direction and confirm hypotheses. It’s a partner to the experience and strategic vision of the leaders.

However, data overload can paralyze some organizations. They may attempt to “boil the ocean” to try and make sense of it all, slowing down decision-making and action. Or they become so overly reliant on data that they constantly await the next batch of data. These organizations end up letting data make decisions for them, vs. using data as an input.

Implication: Use your data as an aide to experience and judgment – and recognize that getting started trumps inactivity

Context-less Data/lack of analysis: Some teams are so busy collecting data, they’re not analyzing or deriving insights from it. They talk about “dashboards”, but aren’t adding layers of context, business, or creativity to yield actionable insights. Without any added business or consumer context, data alone can lead to worse decisions than having none at all.

It’s also important that you’re not just looking at evaluative measures. Knowing that a landing page, an email effort, or whatever is performing above or below a threshold is important but not helpful. Make sure you’re also measuring diagnostic data – datapoints that help understand the “why” behind performance.

Implication: Make sure you add context and qualitative aspects to your data for strategic insights and implications

Metrics replace your strategy: Often teams suffer from “surrogation” – i.e. when they focus so intently on the metrics it has identified to represent their strategy, they lose sight of the original strategy itself. For example, when a company has a goal of having “world class creative”, and they use a quantitative creative testing score to determine what is “world class”. In no time at all, the entire creative process can become more about creating work that passes the copy test than the higher goal of developing breakthrough communications.

Implication: Ensure your data strategy is focused on measuring progress towards a strategic goal

I’ve heard that a better approach to being “data-driven” is being “data-informed” – that this is the happy medium between leveraging experience and instinct only vs. being completely reliant on data. Whatever it’s called, this is the key – using data in conjunction with experience, instinct, and business strategy. And ensuring you are making decisions based on data, but within a larger context of market, users, goals, and vision.

*Originally published in MediaPost’s Marketing Insider 12.20.21

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