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Forget decisions based on gut feeling. Data is the marketer’s best friend.
It gives you the capabilities to target campaigns to segmented audiences, create content based on what we know consumers love, build messages that we know will engage.
Data-driven decision making is our most powerful marketing tool.
Yet with that power, comes more responsibilities. More sources to monitor, figures to crunch, information to decipher into insights.
It’s a tough job.
But someone has to do it.
To help out, I’ve created 5 steps to using data analysis to drive business intelligence. All backed up by our new Playbook, created alongside Hubspot, packed with tips, templates, cheat sheets, and downloads to help you manage your day-to-day information more efficiently.
Before you can plan for the future, you have to first take a look at the past.
This means taking stock of your existing data sources by integrating them into one solution.
One of the biggest issues facing marketers today are data silos - segmented information across your company. 47 percent of marketers suffer from siloed and difficult to access data.
With so many potential customer touchpoints available, managed across several tools, teams end up divided as they rely on different sources of information.
Which means different insights.
A complete solution enables all your users to work off the same playsheet. Helping you align business KPIs and follow a united company vision.
Once you identify the solution, analyze your marketing materials to gather relevant information. The types of sources you need to include are:
This list goes on, including those that are relevant to your company or industry. Your audit should evaluate all the channels you use, the associated information, and the monitoring processes you have in place.
An example of the data sources you could include in your analysis.
Next step, analyze.
Once you’ve amassed an amount of data, you need to turn it into insights - valuable information that you can action.
These insights could be minimal - maybe there’s a social channel that your competitors are using effectively that you’re not.
Or it could be strategy changing - you could identify an issue driving conversations across all media that you’re not tackling. Which leads to new content and new direction.
The key factor is that you use the info that you have. 80% of customer data is untouched. Whether that’s because of silos, or just the inability to handle big data sets effectively, that still means that marketers follow decision making processes based on only 20% of their brand picture.
The best data-driven decision making marketers from recent years didn’t just collect data. They analyzed data, interpreted it, and ultimately, used it for the benefit of their brand.
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Businesses with data-driven strategies drive up to eight times more ROI. That’s what we’re striving to achieve here - more data collection, more actions, more revenue.
Now, with your past analyzed and understood, you can easily integrate it into your strategy, for maximum impact.
A good way to understand it, is that analysis provides the why. In the past, without analytics, you probably knew what processes or campaigns worked. And if repeated verbatim, it could get reliable results time and again.
If you know why it worked. Or how to improve it. Why was that precise campaign or release best? Without this why, you’ll quickly find your strategy repetitive, stifled, and unable to grow. You’ll get stuck repeating yourself until your number dwindle to nothing.
Data, and the understanding it brings, will put life back into your strategy. By pinpointing exactly why a campaign worked (be it timing, audience, content, benefit, whatever), you can break the repetition and bring the ideas that work to everything that you do.
Comparing sales data (blue) against your brand mentions, helps identify which campaigns worked and which didn't.
Next, it’s all about measurement. And yes, that means more data.
Yet, also the right data.
A data-driven strategy often relies on well-informed metrics to measure success. That can even mean different metrics used at different levels of the business.
Take engagement. At ground level, it’s valuable for content and community managers to measure the success of individual campaigns - to identify those that work and those that don’t.
But at a C-suite level, engagement means little. Here you need to be tying your marketing efforts into business impact metrics. The figures that are driving results for the brand (typically revenue or sales).
If one campaign went viral, that’s good. But if you can demonstrate that virality increased share of market, leading to an uptake in sales, that’s great.
Data-driven marketing isn’t just about creating success, but demonstrating that success within the company.
Finally, you need to report your results effectively.
A clear reporting strategy is the difference between being successful, and your boss knowing that you are
Like the monitoring section above, making sure you
And remember - reporting is not the end of the data-driven journey. You need to use it to find the takeaways that you can feedback into your strategy - for further analysis and insights. If a campaign falls flat, but by the end of it you’ve learned a valuable insight for the future, it’s far from a total failure.
One key skill a marketer needs, is the ability to learn from mistakes.
Data driven decision making is the future of marketing. Enabling brands to engage audiences more personally, create more targeted content, identify issues, and more. To be a success, it’s time we all became data scientists - taking the raw blocks of information we have, and building global award-winning campaigns.
Grab your marketing manager playbook below to enable your strategy.