When big data started taking off around 2005, businesses gained access to vast amounts of information about customers, finances, and day-to-day operations. But having all that data did not mean people, especially marketing teams, used it. Many still make decisions based on gut instinct, whoever speaks the loudest in a meeting, or what they did last month. That reflects a real issue rooted in a lack of culture.
At Connection Model, we help you understand analytics-driven marketing and build an effective marketing analytics strategy.
The first thing you should know is that a data-driven culture isn't measured by how much information you collect, but by how often that information influences decisions. In a healthy analytics culture, data is part of everyday conversations. Often, that cannot happen because of the following roadblocks:
Technology can make information easier to collect, organize, and understand. However, culture comes from people. To build a data-driven one, follow these steps:
If leaders want marketers to take data seriously, they must demonstrate that behavior themselves. They should also ensure teams have the training and tools they need to work with data confidently.
One of the easiest ways to overwhelm a marketing team is to measure everything simply because you can. Instead, know what you are measuring, why you are measuring it, and how the number informs the business.
Vanity Metrics vs Decision-Driving Metrics: Vanity metrics like follower counts, page views, impressions, or total downloads can look fantastic on a report. They aren't completely useless, but they rarely help you decide what to measure next.
Decision-driving metrics, by contrast, connect actions to outcomes. Those are the kinds of insights marketers can act on.
There is not one universal list of “correct” metrics. Your job is to figure out which numbers genuinely help your team decide what matters most.
Aligning KPIs to Business Outcomes, Not Activity: A useful KPI is something you can trace from an individual metric to a department objective, then to the organization’s strategy, and finally to its broader mission. So, start by identifying what the business is actually trying to accomplish.
Then, turn those priorities into specific objectives. Once you know what success looks like, choose KPIs that clearly show whether you are getting there.
If someone needs information to do their job, they should not have to ask everyone on the team to see it. Moreover, keep in mind that a dashboard should inspire action.
When creating a dashboard, define the objective and audience. Then, select the metrics and data sources that actually support that purpose. Also, put the most important information first, and use visual hierarchy to make the story easy to follow.
Again, in a healthy data-driven culture, data is part of everyday conversations. That means you should set weekly, monthly, and quarterly reviews.
Every week, evaluate immediate performance and emerging problems. Every month, look for trends and adjust campaigns or budgets. Every quarter, evaluate whether your marketing analytics strategy is actually supporting your business goals.
Before any meeting begins, you must already have a clear agenda. Prepare a few talking points, and finish with actual next steps.
In some organizations, the most senior person in the room automatically wins the argument. If you want an analytics culture, change that dynamic.
Normalize acknowledging that the data doesn't support a decision without thinking you are challenging someone’s authority. Reward those who change course when the evidence points elsewhere.
From a technology standpoint, you do not necessarily need a giant stack of platforms. Go for tools that generally make information accessible, such as the following:
Getting buy-in is a huge part of any analytics-driven marketing process. As such, it is crucial to make data feel useful rather than threatening. So, how do you do that?
Let your marketers communicate their frustrations and confusion and genuinely understand them. Then, make training fun through friendly competitions and small challenges. A little bragging-rights energy can make learning a new system much less painful.
Ultimately, analytics are only valuable when they drive decisions. If you need help with reporting infrastructure, dashboards, and review cadences that turn data into a competitive advantage, turn to Connection Model. Reach out today for a free consultation, and let us build a smarter foundation for your marketing team.