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Adding Real Value With Thought Leadership and Data (Part Two)

In part one of this blog series, we discovered why data and thought leadership go hand in hand. If you haven’t had a chance to read part one yet, here’s the link to find out more.

In part two, we’ll explore how we can use the correct type of data to add value and credibility to your thought leadership strategy.

Let’s dive in and find out how this can be achieved.

Conducting new, relevant and timely research can present huge advantages within any thought leadership content strategy. Using out of date data, perhaps initiated for a different purpose, won’t be as compelling and could lead to misinterpreted conclusions. Conducting new research, which is fit for purpose, can offer new insights that can be applied to existing challenges – and create a killer piece of content too!

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So how can quantitative and qualitative research best be utilised for this?

Quantitative research is probably the most common form of research and relies on large sample sizes to present facts and uncover headline trends. The data is usually gathered through online surveys so that large audiences can be targeted quickly but effectively.

This allows attitudes, opinions and behaviours to be explored and uncovers meaningful statistics or trends; the perfect combination for embedding robust data into compelling thought leadership content.

Alternatively, qualitative research uses smaller sample sizes and conducts interviews on semi structured questionnaires. This data collection method offers a human touch and brings the numbers to life with valuable viewpoints; in particular, face-to-face interviews and focus groups help uncover deeper insights on a specific topic, but this method can be harder to replicate on a larger scale.

If you’re interested in finding out more about the different types of data, take a look at our data deep dive.

Using a combination of the two types of research can be a valuable way to improve and substantiate research findings. Supplementing small samples of qualitative research with a variety of quantitative findings is a great combination to produce rich content that can help the C-Suite to develop ideas and validate hypotheses.

Bringing data into the bigger picture

When executed correctly, thought leadership content supported by quantitative or qualitative research, or even the combination of both, can create killer content; after all Content is King! It can position you and your company as leaders in your field, find new sales leads and ultimately, build lasting relationships with your target audience.

If you’re interested in finding out more how to increase your thought leadership ROI, take a look at our six ways data-driven approaches can help.

Don’t simply show your data, tell a story with it!

Once you have successfully collected and combined all types of data, the next step is to extract value from it. Use your data to tell your audience a story, guiding them through the problem, action and solution. This is how you can really bring your data to life and drive your readers to take the next steps.

Of course, becoming a leading expert in your field doesn’t happen overnight. There’s a lot of work that goes into creating a data-driven thought leadership strategy, so we’ll leave you with our key takeaways.

1. Consider your key messages

It’s important to understand what your key messages are and how you can support these messages with opinions from your subject matter expert and ultimately back them up with evidence.

2. Pick the right data research method

Choose the correct way of collecting data that will deliver the desirable results. One method might have benefits over the other, or alternatively using qualitative and quantitative methods together might strengthen your findings. Consider which methods will work best to produce your data-driven thought leadership content.

3. Never stand still

Be on your toes. Always look out for what’s changing in the industry, by reacting and weaving news into your thought leadership strategy with the help of data.

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