Imagine having the ability to know exactly what your audience is saying about your business or service. Go one step further, and imagine having the ability to know the specific interests of your customers — insights you could use to better target other potential customers with those same interests. That would be powerful data for any business owner to have, right?
Data gathering and analysis are important marketing trends in 2017, and obtaining the data mentioned above is possible simply by mining the conversations people are having on social media sites.
While attending Inbound 2016 I had the pleasure of attending a presentation about data mining with Jason Falls. He explained not only the benefits of using social conversations as baselines for conducting research, but also how doing so better informs business owners about their audience. In this blog post, I’ll share what you need to know to effectively analyze social conversations to inform your marketing strategy.
Social monitoring vs. social listening
While social monitoring and social listening sound alike, they can mean very different things.
Social media monitoring is considered reactive listening. This means you are actively monitoring for something specific online, be it a phrase or your company's name. You’re waiting for the mention and then will react to it.
Social media listening, however, is proactively going after people talking about specific topics or trends and trying to understand the commonalities between individuals talking about those topics. You can also use social listening to find a gap in the market; maybe several specific people are in need of something and are actively searching for it.
Why would you use social data?
We’ve now come to the root question: Why would I do this for myself? The answer is simple: Social conversation data gives you the ability to mine information in real time, from real people, on a variety of topics. This data can inform your decisions as a marketer. Now, instead of assuming what your audience wants, you can make data-informed decisions.
In general, most social media listening data is used to inform product decisions, improve customer service, and market a product. In regards to product, social monitoring can help you understand what your audience is saying about a newly released product and recognize if you need to make any changes. Social listening can also help your company recognize if there is a gap in the market you can fill with a product or service.
Customer experience can also be positively affected by social monitoring. Recognizing if your customers are experiencing an issue with a process you have have in place can be huge for improving your overall conversions. By improving your customer experience you can also improve your overall brand image.
How you position your product or service can be influenced by the insights you gain from social data. Social data has the ability to give you a deep level of understanding about your audience — far beyond the traditional age, gender and ethnicity. You can learn other interests your audience may have so you can target other like-minded individuals. Using this information to target your audience in a new way with relevant content can help gain customers.
Sentiment is another important factor you can track using social data. Seeing how individuals talk about a topic can help drive your marketing strategy. If the perception changes during a certain time you can intelligently reposition your product to match. Considering where individuals are talking about your brand or service can help you explore additional advertising opportunities for your brand so that you stay top of mind.
How can you conduct your own social conversation research?
Now that you’ve learned the why, let’s examine the how.
Traditional research is complex and structured. If you’re writing a survey, you typically have your subjects follow a specific structure. If you’re conducting in-person research there is subject bias because you’re picking individuals who fit a specific, pre-determined qualification. In direct contrast, social research is unstructured; you’re getting unsolicited feedback from people who actively want to share their experience, opinions, or feelings, which helps remove any subject bias.
When you begin to analyze your social media listening data expect that you’ll start with a lot of data and information. This means you’ll have to “clean” what you get to ensure you are filtering out the information you don’t want.
So how do you sort through the data to get the insights? Follow this five-step process:
- Questions: Ask yourself what you are trying to find with this data. Are you trying to see what your consumers are saying about a specific product you offer? Do you want to see what a particular audience finds important? Really drill down into specifics before you collect the information.
- Collection: You’ll use the program of your choice to collect the data.
- Disambiguation: This is where you begin to sort through the data to find what you really want. This means removing any press releases that aren’t considered genuine reactions, any re-posts of those press releases, and any other mentions that aren’t relevant to your search. You can easily remove these by setting up a scoring strategy for the data. But remember that no manual sorting or scoring will be as good as your judgement, so don’t forget to take the time to dig in and look at your results. The good news is that this part of the process will take about 90 percent of the time and effort, so once you’ve finished you’re almost done!
- Exploration: Once you have the data scored and the information in front of you, it’s time to start digging in. What is the information telling you, and what questions is it answering about your data?
- Insights: You’ve reached the final step, where you have the data and you can start making informed decisions based off of it.
A few helpful notes about this whole process: as with most research, what you get may be completely different than what you expected to get. Don’t be afraid to change course if you uncover something completely unexpected but still helpful to your ultimate goal.
If you’re having trouble trying to analyze the data, checking for spikes in the data or comparing it to competitor information is another great place to look for insights.
Finally, if you’re having trouble determining what to really look for, you can always use the “framework of curiosity” Jason Falls recommended:
- Form: What does it look like?
- Function: How does it work?
- Change: How does it evolve?
- Perspective: How is it impacted?
- Cause: Why is it like this?
- Reflection: How do I know?
- Recommendation: What now?
What other questions or comments do you have about data acquired from social conversations? Be sure to leave them in the comments below!