How to Analyse Data to get to More Inspiring Insights

To gain insight into a something or someone, or to solve a complex problem, you need to gather data.  This will provide a more accurate or deeper understanding of the problem or person. Insight is understanding, discerned through data that has collected and analysed.

Data is a collection of facts which form the building blocks of insight.  These can be observations, words, movements, numbers, patterns, or places.   Data forms numerical and visual patterns that shows us where the gaps are, for instance, where markets are overserved or underserved and how changes in a business affects customers, markets and profit. For more on this review data analytics and insights.

You can think of data as big data, the kind that businesses collect to determine the cause of problems, who is buying and when, and how to market more effectively.  Data can also be small.  Where big data is about machines, velocity and volume, small data is about people, taking time and answering the why question.  Small data is critical for the insight that lies behind trends in big data and provides a more actionable way to market to target audiences.

How to collect insight data

Collecting the right data to answer your question is essential. In market research we collect different forms of data – qualitative and quantitative.   These two different types of data provide different insight through different forms of interpretation.

1. Quantitative data is survey data. The data is more objective, numerical, structured and can be either continuous – as in tracking data points across time – or discrete to serve the needs of a particular study such as a market sizing study.  Big data tends to be quantitative in nature but not all quantitative data is big data.
2. Qualitative data is drawn from focus groups, interviews or observational research. The data is subjective, interpreted through observation, listening and conversation, the reading of text, the watching of video and can also be either discrete or continuous – observing people over time. Small data is qualitative which allows for great depth and understanding.

The process of conducting the research relies on interpreting the data – either big or small. Throughout the data collection process (or fieldwork) you can be collecting insight as well as data.

Sometimes insight can happen even prior to the fieldwork, by merely considering the problem or researching the right questions to ask.  But the most important time in finding insight usually occurs at the time of analysis, where time is set aside to review the facts, observations, and data and consider what this all means in solving the problem at hand.

Use an Analysis Plan to Keep on Track

It is important to have your analysis plan or tools ready as the research proceeds, so that you can download important ideas, facts and considerations as you go. As insights can come at any time, do not wait until you have completed the research to write your plan.

An analysis plan which is focused on answering the key objectives will help keep you on track. Analysis paralysis is a term many researchers use to describe the feeling of being overwhelmed by data to the point where it is hard to get started, keep going or draw meaningful conclusions.

Creating an analysis plan will:

• Outline the objectives and how you want to answer these with your data
• Ensure you have asked the right questions or made the right observations to answer your questions – and if not, can remedy the situation
• Help you funnel data into themes and then ultimately insight to inform better decision making
• Make you contemplate clearer and more accurate conclusions – for instance have we seen these patterns before, what could be influencing the patterns?

Creating an analysis plan for inspiration insight

Create an analysis plan to simplify the analysis process and improve your data analysis skills. A simple plan might have 5 or 6 steps but each one should think about the following:

1. Consider the bigger picture

• What are the key objectives of the research that you need to crack? What decisions will be made because of the research?   How will the client use the research now and into the future? Is there a way to approach these objectives in a structured way that will help create a story?

2. Spontaneous Surprises:

• What came up that you never expected to find? Spend some time brainstorming why and how this data arrived and if it is meaningful or distracting?  Is there a reason there were no surprises and is this worth exploring?

3. Key Themes

• It’s important to start with the big themes to understand the bigger ideas first.
• What are the emerging patterns from your data? If you could chunk these up into key themes, what would this look like?  Perhaps there are meta themes and sub themes and you could visualize these in a tree or a flow chart.

4. Digging into the Data

• Granularity is important as this is where the gems might lurk. It may be that you create several different analysis options to play with the data and see what washes up.
• Or it could be about breaking your key themes emerging from the data into smaller chunks and ask why that is happening. What does this mean? What is the meaning behind the meaning? How does this impact different segments, behaviours, motivations or attitudes?  What is the implication of the meaning behind the meaning for the business or brand?

5. Time to Derive Insight

• What does your data tell you that people want, believe, need? What story does the data tell us that we didn’t know before and how should that impact decision making? How can we present the data in a way that makes the insight crystal clear – visually, aurally, or through storytelling?

6. Draw Conclusions

• How does the data driven insight shift the needle on thinking for the business or brand? What is the aha effect that we didn’t know before, or that we have confirmed?  What do we need to recommend as a result of our findings?

The analysis plan is not the findings and not the story.  It is a plan that will help guide your analysis to make better use of your time and allow you to think about insight.  Come back to the plan several times as you work through your analysis and test your thinking.  If there is more than person working on the project you should all be working to the same plan, so make sure it works across all areas of the project, or is broken down into discrete units where required.

In Summary

To get your data fit for inspiring insight, you need an analysis plan.  Planning will help you focus on the things that matter and keep you out of the weeds.  Inspiration can come at any time so remember to think about outcomes before you start the collecting process.

Want to know more?  Drop us a line at info@rubychacha.com.au or call us on 80946801.