Forty-nine percent of marketers around the world report that they struggle to turn data into value or insight. That’s not surprising when you consider 79 percent of them said the skills and capabilities within their teams were very weak (34 percent) or weak (42 percent) when it comes to data. (Source: SoDA Report)
Initially I was surprised, but after reflection, I realized that my personal experience over the last 10 years has told a similar story. Few of my clients have realized the potential of their data.
Let’s get one thing straight – big data isn’t the answer
Big data is a theoretical concept that is poorly defined and not much more than a buzzword. When you read about “big data” it’s often about marketing automation, sophisticated data mining, and the challenges of gigantic piles of endless data.
In 2012, Gartner updated its definition to the following: “Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.” (Source: http://en.wikipedia.org/wiki/Big_data)
As a marketer, try to not let that excite or distract you. It really is just a buzzword, so let’s be more practical.
What I’m talking about is data marketing
That’s the act of utilizing data to make smarter decisions, which as a result, leads to improved marketing goals. Let’s narrow our focus even further; we’re talking specifically about using the data we can capture on a person’s behavior.
7 steps to data marketing fitness
1. Clear goals
Be very clear about your business goals and KPIs; if you don’t have clarity on the end goal of your data marketing, huge amounts of effort can be wasted. Think about whether you’re looking to increase customer retention, increase spend per customer, attract a new segment of customers, or shift perception of a brand to drive purchase of a new product.
2. Quality over quantity
Inaccurate, disparate, or out-of-date data is often worthless, so it’s important that you analyze the quality of your current data assets. How old are your email contacts? Is your website being tracked properly? Do you have meaningful customer information? Are you collecting data for the sake of it, or does a single data point have a clear value? Having multiple data sets about your customer that don’t link up or contradict each other will be your next challenge, so get it all tidied up.
Once you get to this step, it’s important to stop and ask yourself what data is actually needed, and more importantly, what you are capable of analyzing as a business. I know of many brands that capture information about customers but haven’t used it, because they don’t have the skills or time.
3. People powered
Next, you need to consider the talent within your business or agency. Who is the expert on your data sets and who has the vision for how they come together? Your data experts are essential in conducting in-depth analysis of the data, but more importantly, in maintaining the data’s quality and the technology to support it.
These people, known as “Data Scientists” are in high demand and in extremely short supply globally. Be clear on who your data expert is; get to know them and make sure they understand your overarching business and marketing strategy.
Basic data analysis is a process of reviewing data, asking why, and forming a hypothesis until a meaningful and actionable insight reveals itself. Without asking why, you’re making assumptions, which can quickly lead you nowhere.
Now we move on to tech. Wow, it’s an epic world of tools, platforms, and confusion. The tools available either provide you with more data, organize it better, or enable analysis into meaningful insights.
The tools we use most regularly fall into 10 broad categories:
- Website analytics
- Mobile app analytics
- Online surveys
- Experience analytics
- Tag management
- CMS reporting
- Competitive intelligence
I’ll be following up with a post in the next edition of my column with some of the best tools going around.
I’ve included links to some well-known tools and highlighted the ones our data team uses on a regular basis. Please note, this is just a short list, and I’ve been very crude with my categorization of them as some cross multiple categories.
5. Filter the noise
A recent major study by CEB found that the highest performing marketers around the globe all had an ability to focus. The three key qualities they shared were “comfort with ambiguity, ability to ask strategic questions based on data, and having a narrow focus on higher-order goals.” (Source: HBR)
Each data set you create is full of noise and meaningless information, which doesn’t lead to making smarter decisions. Your challenge moving forward is to continuously cut out the data clutter. If you think a piece of data is interesting then cut it out, if you change your behavior based on a piece of data then keep an eye on it.
6. Align to goals
After auditing your current data, identify your data expert(s), and update new data sets where required – it’s critical to review how this will help you achieve your overall goals and KPIs, as it’s easy to get distracted with your shiny new and seemingly smart data marketing setup.
7. Analyze, decide, act, monitor, and repeat
Finally, you’ve actually started. Now it’s time to set up an ongoing process that ensures you analyze your data in meaningful and well-organized reports, make decisions on that data, act on those decisions, monitor what impact those decisions made, and repeat.
Over time you’ll realize your data marketing fitness will have improved dramatically and hopefully you’ll be making much smarter decisions without even realizing it.
Marketing technology vendors must cut through the big data illusion and make its core principles easier and more applicable.
WeChat started out as a social messaging app but has become an essential part of an integrated online and offline (O2O) ecommerce strategy for brands operating in China.
Have we been measuring content the wrong way? Inbar Yagur, Senior Content Strategist at Taboola, gave a talk at the Content Marketing ... read more