The Challenges of Data-Driven Marketing (And How to Overcome Them)
More businesses are turning towards data-driven marketing to help them better align their strategies with consumer behavior. A lot can be gained from using data to inform marketing decisions, but it doesn't come without its challenges. This article outlines some of the most common challenges of data-driven marketing, along with strategies to minimize and avoid them.
In the marketing world, data is everything – especially data about your campaign’s audience. It’s the scaffolding that supports your efforts and guides the shape of your marketing campaigns as you build them. When you think about it, data is the one thing that turns your marketing strategy from “a shot in the dark” into an informed initiative designed to capture customers and grow your business. With data, marketers can segment their audiences to create relevant, personalized messaging, evaluate the success of a given campaign, and improve the overall efficiency of their campaigns. The only catch? Data-driven marketing – like everything in life – comes with challenges.
The first step in overcoming data-driven marketing hurdles is to understand them. Only then can you build a plan to remove roadblocks and streamline your process. Here are a few of the most common data-related mishaps in the marketing space, along with strategies to minimize and avoid them:
Integrating data from multiple platforms
Any marketing strategy worth its salt involves data from multiple sources, and multiple sources means varying formats. There are two potential challenges with this scenario: The data you collect from many sources could be inconsistent, and the tools you use to aggregate that data are probably complicated.
Imagine asking two people for directions. The first explains your destination is one way while the second tells you it’s the other. That’s what it feels like when your data sources yield (seemingly) contradictory information. You want to use data to guide decisions - but which direction should your marketing strategy go? This is where data cleaning comes in.
In short, data cleaning is the process of identifying and eliminating factors that can skew information and create those annoying discrepancies between sources. To ensure your data is clean, always check for duplicates, scrutinize the logic behind it, and be consistent in the way you organize your data. (Don’t use “December” when most reports say “Dec,” for instance).
Making sure you data is clean and complete
Let’s revisit our directions analogy. If you ask one person for help but they only direct you halfway to your destination, you’re not going to reach your objective. The same thing goes for data. Even worse, what if the directions you got are just plain wrong? In the same way, data quality is imperative for marketers. According to research, however, 64% of marketers cited “improving data quality” as the single biggest challenge they encounter when attempting to personalize messaging for audiences. To make yourself part of the 26% that don’t worry about data quality, create a process to stave off inconsistencies and keep your data up-to-date.
Measuring the right KPIs
Every piece of data you track should serve a purpose. In fact, tracking data without a clear purpose is a waste of time. Lucky for marketers, finding valuable KPIs (key performance indicators) is relatively simple; all it takes is a little planning:
- Identify your organization’s overarching goals
- Figure out what data points contribute to these objectives
- Create a plan to re-evaluate your KPIs
- Don’t be afraid to add new KPIs or remove outdated ones
When dealing with KPIs, it’s important to avoid getting caught up in vanity metrics. Simply put, vanity metrics are pieces of information that might seem impressive but don’t truly contribute to your objectives. The same goes for duplicative metrics, or “performance” indicators that don’t actually reflect performance quality at all.
Finding actionable data
Your data should be actionable. Always. The best way to understand actionable data is to consider its sinister counterpart: ineffective data. The easiest way to identify data that won’t help you is to ask the question, “Okay, what do we do with this information?” If you can easily identify the next step, the data is actionable. If not, dig a little deeper and figure out if it’s actually worth tracking, measuring, and serving to stakeholders.
Actionable data allows you to identify patterns, correlations, and relevant relationships between data sets. Often, the first step in finding data that provides this level of insight is to increase your understanding of your own goals as a marketer. Does the data help you understand what resonates with customers or clients? Does it produce a positive ROI?
To expedite the process, consider using a data visualization tool to identify hidden correlations between data sets, and to speed up the time it takes to understand large data sets across multiple platforms.
Inadequate tools
In data-driven marketing, few things are as detrimental to your strategy as unsupportive leadership and restrictive budgets. But inadequate, poorly maintained, or broken tools are another serious hurdle. In marketing, inadequate tools can actually contribute to many of the challenges mentioned above – from contradictory reports to poorly integrated data sets from multiple interfaces. As a marketer, you need to create a single source of truth where you, your team, and your boss can find common ground in data. That’s why it is imperative to spend time to determine which tools are right for your department and their goals. Then, you can turn that data into an actionable, informed marketing strategy for your organization.