Unpicking the tangled mess of B2B data
Judith Niederschelp, MD at Aberdeen Group Europe, attempts to untangle the mess that is B2B data
According to recent research from Aberdeen Group, 48 per cent of B2B marketers are fighting a losing battle against disorderly data.
This 48 per cent breaks down into marketers who ‘don’t know where to start’ (six per cent), ‘aren’t able to track and report effectively’ (six per cent) or who ‘track more than they can act on effectively’ (11 per cent). The remaining 25 per cent ‘have trouble tracking and skew reporting with opinion’.
The statistics point towards a lack of ability and a lack of confidence. And this results in a failure to collect basic data on marketing efforts via tracking, or to use that data to drive value through reporting.
But all is not lost.
Data-driven marketing always starts with a confusing tangled up mess. Once you acknowledge this, it’s possible to see past it. And once you see past it, you can begin to tackle it, one step at a time.
Step 1: Establish data literacy
Data literacy is about knowledge, not opinion. It’s about ascertaining what the data is indicating and communicating that to others confidently and accurately.
When dealing with data, it’s important to take a methodical, objective approach. Try focusing on questions such as:
- When was the data collected? Is it still relevant?
- Where was it collected? Did it come from a reliable source?
- How was it collected? Was it compiled in a reliable manner?
- What does it mean? Does the data offer any definite conclusions?
- Why does it mean what it means? Is there more data to support these conclusions?
Step 2: Define data utility
Before spending time collecting and analysing data, think about how it’s going to be used, and how it will add value. This enables efforts to be focused on the most relevant, appropriate data.
For instance, if you want to measure the performance of content assets sent by sales reps to marketing qualified leads, social sharing data will be irrelevant. To determine the effectiveness of the content, you need access to data that is tied to the business goal. In this case, you’d explore how prospects who received the content performed in the sales process.
Step 3: Experiment with data
Testing and experimentation go hand-in-hand with data-driven marketing.
Build on the value of data by conducting controlled, manageable experiments to test marketing hypotheses and evaluate tactical options. Collect basic data on what’s happening now; propose ways to drive improvement; then test, tweak and repeat.
Over time, this approach enables marketing to be refined and precisely crafted to drive desired outcomes.
Step 4: Expand into new realms of data
It’s so easy to find yourself overwhelmed by data-driven marketing. One of the most common mistakes is to take on too much too soon. The goal should be to improve marketing performance in a measurable, predictable and reliable way over the course of months and years.
The best way to achieve this is to start with the data you already have a handle on. In many cases, this will be data derived from basic internal marketing metrics. Once you’re comfortable working with that, extend the reach of your activity. The next step might be to look at content consumption data to identify patterns. Once those patterns are understood, they can be used for lead scoring, and so on.
If you’re in the 48 per cent of marketers who find their data unusable or unfathomable, take a step back and re-evaluate the situation. By tackling and mastering one area at a time, you can gradually get it under control.
Keep it up, and you’ll find that you are able to build strong foundations for sophisticated data-driven marketing that is continually improving.