Direct Marketing News recently published an excellent thought-piece 'Can Marketers and Data Get Along?' Editor-in-chief Ginger Conlon cites the disconnect between data scientists and marketers, and explores why marketers aren’t benefitting from the insight available to them.
Here Infotools provide five quick tips for insight departments. Use them to make sure your data gets used by the marketing team.
1. Data organisation
Consumers are messy. Researchers and data scientists love to put them in boxes, but human beings don’t always fit neatly. Preparing data by checking, categorising, labelling and recoding into logical categories can make a database many times more useful.
Collating all sources of consumer and marketing data in one place not only means data can be cross-analysed, but also removes a massive headache for the data custodian. Even when staff move on, data can always be found.
2. Speedy turnaround
Relevance is key to keeping the attention of busy stakeholders. Involve the marketing department in the planning stages, and then show them the results of their input as quickly as possible.
A good way to save time is to decide what you want to see in advance of having the data. When deciding what questions to ask or what data to include, think about what business questions it will answer, and how you’ll need to see the data in order to answer those questions. For example, a recommendation score out of 10 might generate these questions:
- Are people more likely to recommend us in branches where we introduced a customer service initiative?
- Are there differences in likelihood to recommend us by region?
- If so, what are the unique beliefs people hold about us in our most successful regions?
To answer the first question, you could view the percentage who recommend in branches where the customer service initiative was introduced, and those where it wasn't introduced. You’d want statistically significant difference between the bars to be shown.
Above : A simple chart with significance testing can show us if customers are more likely to recommend in branches with our customer service initiative.
For the second question, you might want to see a shaded map where the colour represents the strength of recommendation in different regions.
Above : A shaded map helps us see where recommendation is strongest.
For the third question, you might want to see a correspondence map of our image attributes and our regions.
Nothing is stopping you from planning out these views in advance, ready to be populated with data when it arrives.
3. Engaging presentation which encourages interaction
Just as good branding enhances the value we feel we get from a product, good presentation enhances the credibility of insight. Of course the data is more important than aesthetics, but why make people work hard to understand it? We need to get the insight right, sure, but just as important is getting it used.
This is where data visualization comes in. Data visualization in a nutshell means 'well-thought-out charts.'
The latest platforms for data visualization not only present data flexibly, clearly and attractively, but they also encourage your audience to interact with the information.
This is important because when we manipulate data for ourselves, our attention levels increase. We begin to ask questions and engage with the subject. We’re more likely to remember and act on the insight, because we’ve taken part in discovering it.
'This report, by its very length, defends itself against the risk of being read,' said Winston Churchill.
The best way to ensure consumer insights are not read is to bury them in a fifty-slide PowerPoint deck. Marketers in particular are used to effective communication, and so they have little patience for irrelevant information.
Prepare your story, using just the information relevant to the point you’re making. Structure it around marketing questions, not research questions. Make your point clearly and don’t expect your audience to have to go looking for the data.
Of course, people in your organisation who are data explorers should be given the ability to interact and delve deeper into the data. Ideally, we want to give different levels of functionality to different people.
Examples of simple interactivity include demographic filters and switching between charts and tables. More advanced interactivity would be changing the metrics charted, ranking, changing the default significance testing, etc.
5. Capability to collaborate and exchange ideas
So you’ve got your marketing department’s attention. Now to get some action.
The best ideas don’t happen in a vacuum, and neither do ideas for responding to consumer insights. By making it easy for your audience to share charts, add notes, and reply to each other’s comments, you can generate momentum around the findings.
Social sharing functionality is a common feature of newer data visualization platforms. These are often cloud-based, so you can share a link to a chart or view you’ve created and someone else can comment on it. If you update the chart, they see the updated version too – avoiding multiple versions of reports floating around or stored in Outlook inboxes.
In summary …
The best consumer insight in the world is nothing unless it inspires in marketers the confidence to act. We can make this happen by …
- Preparing our database so it’s easy to use
- Planning our reporting so it’s quick to deliver
- Using data visualization to engage our audience
- Giving relevant insight – and nothing but relevant insight – to the right people
- Making it easy for our audience to exchange thoughts and plans based on our insight.