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5 ways to think bigger when it comes to social data

by Kate Radway | Mar 27, 2018

This post was originally created by Spredfast before Spredfast and Lithium merged and became Khoros.

If you’re not using social data to inform the biggest decisions at your organization, then you’re not thinking big enough. Most organizations leverage social data to make decisions about social: Do I post more of cats or dogs? Some organizations leverage social data to make decisions about messaging: Do we include copy around hiking for exercise or hiking for self-reflection? Very few organizations use social to make decisions about big things like product development or brand position. You want to be one of those companies that use social media data to help inform your big decisions.

Why use social media data and social data science?

Companies that are smart enough to use social media data mining, social media data collection, and social media data analytics (see definitions below) understand that the always-on focus group of social circumvents both the time and cost of market research. This social data is more responsive to emerging trends and the changing behavior of consumers. The companies that use social media data intelligently are in touch with their audiences’ wants and needs — and what marketer wouldn’t want that?

We’re not saying you should throw out traditional information gathering channels. Keep the focus groups. Rather, social data should be presented alongside what Sophie and Owen said in your Chicago listening session. Using social insights and social data science while crafting your next global marketing campaign — or even when developing your next product line — will help you make better, more informed decisions.

Social media data definitions guide

Social media data mining

This is the first step of the process. It involves collecting social data from user-generated content on social media sites and mobile apps.

Social media data collection

Once the data has been mined, the collection process involves organizing and preparing the data. This will set the foundation for the analysis step of the process.

Social media data analytics

Now that your social media data has been mined, collected, and organized, you can begin to analyze, identify patterns, formulate hypotheses, and draw conclusions.

Using social insights while crafting a global marketing campaign will lead to more informed decisions.

Here are five specific ways to think bigger when it comes to leveraging social information in your organization.

1. Move beyond your brand to start tracking the things that impact you

You can monitor brand mentions all you want, but if you aren’t also monitoring the larger factors that affect your business and practicing consistent social media data collection, you will miss key signals and social media data that could impact your bottom line. What does your organization depend on? If you sell any packaged food items, for example, you should be tracking and reporting on what health publications are sharing on social—and what’s getting interest. If you’re a retail brand, you should be evaluating retail-tainment activations in stores of your competitors. If you are in financial services, you should be listening to everything from how people talk about money on social media to how people respond to the financial markets in general.

If you’re able to detect a shift at the top of your funnel, you will have the time you need to evaluate the impact it will have on your business. This means smarter, better planning.

2. Develop and test hypotheses around consumer motivations

You can’t be passive with social data. Industry-changing ideas aren’t going to come out of a hashtag search (believe me, I’ve tried). Think about what you believe to be true about the motivations of your audience—and then test those assumptions. You may be right, which is a great vote of confidence to continue what you are doing. But you may be wrong and the more quickly you can adjust, the better positioned you will be compared to your competitors. Monitor your social media data analytics regularly to bolster your development and testing strategies.

Here are just a few examples of the types of hypotheses that can be tested with social data.

  • Hypothesis: Protein is still closely associated with strong, bigger muscles
  • Hypothesis: Young mothers drink caffeine because of the jolt of energy needed to accomplish their massive to-do lists
  • Hypothesis: Cycling is a fitness trend that is still isolated on the coasts
  • Hypothesis: Consumers visit brick-and-mortar stores because it’s a social activity

Too many marketers expect social data to deliver eye-opening insights without ever thinking about the questions they are asking. If you ask the right question of your social media data, you’re going to get better results.

3. Track passion, regardless of industry

One way to start is by following cult brands and the people that love them. You might say “Pshh, I’m already following brands that inspire me.” Sure, you track their posts, but do also spend time learning from their followers? Social media data collection gained from monitoring a brand’s followers can divulge new insights and information that you would otherwise be unable to obtain and organize.

Once or twice a year, pick five brands with enviable communities. Conduct a deep analysis. What motivates their followers to post? What causes them to profess their love? What do they celebrate about the brand? What do they talk to each other about?

Once you’ve done this, you can look at the community your brand is fostering and ask the same questions. What are you missing that these iconic brands have brought out in their audience? Monitoring this kind of social media activity, through the lens of social data science, will help to give you a roadmap for success when building belonging amongst your base.

4. Don’t be afraid of extrapolation

Organizations are often more comfortable taking a handful of voices from a focus group and using their opinions to adjust brand positioning than they are taking thousands of social posts and doing the same thing. People like to list caveats about how social behavior isn’t real behavior and how Instagram lives are filtered, both literally and figuratively. This shouldn’t keep us from using social media data mining as a cultural touchpoint. The size of the data pool alone is what makes these insights, even if they are filtered, so compelling.

For analysis purposes, I like to think of social curation as projecting your desired state. Let’s consider the following example. When you look at hashtags around vacations (#familytrip, #couplestrip, #girlstrip and #solotrip), you see a dominating conversation.

Does this tell us that more people take friend trips than take family vacations or go on trips with their significant other? No, probably not. What it does show is that the act of sharing when you are on a trip with your friends is more appealing within our culture at the moment. A hospitality brand can take advantage of this by appealing to themes of togetherness, friendship and bonding when creating campaigns to generate interest and increase bookings.

The idea of projecting your desired state is that what people are sharing is tied to a cultural ideal of what’s valued. Asking what is behind the social content and why people are posting it can lead you to interesting observations and new social data science avenues that can only be found outside of the words and hashtags used in the posts.

5. Use these three questions more often:

  • What does this mean for our messaging?
  • What does this mean for our brand positioning?
  • What does this mean for our products?

The regular reports you get on social media performance aren’t going far enough. A typical report might include overall numbers around keywords and hashtags, simple takeaways on what content is performing well and maybe a line about themes you can carry into next quarter. Require your social team to answer the three questions above in all regular reporting. A quick example on what this looks like in practice: Instead of reporting simply that posts containing dogs regularly over-perform content benchmarks for an outdoor retail brand, consider something like this:

What does this mean for our messaging? We should create a brand persona of a hiker that has a dog and regularly goes hiking with their pet. In our messaging, we should stress themes of friendship and companionship that a pet can provide.

What does this mean for our brand positioning? We aren’t just the brand for you, we are a brand for your family, even if that family is furry and has four legs.

What does this mean for our products? We should consider the needs of pets in our outdoor products. What does a consumer need for their dog in our different product categories?

It is easy to assume these takeaways are self-evident in the line “posts containing dogs regularly over-perform for our brand” but in practice, people rarely act on unspoken insights. The practice of answering these questions explicitly will lead you to a deeper analysis that can have a big impact on your organization.

Redefine how you use social media data

Now that we have a better understanding of how social media data can guide large scale decisions and strategies, we encourage you to adopt these ideas and begin to evolve your big picture thought process.

If you would like to learn more about how to utilize social data for your organization or how the Khoros platform can manage and deliver crucial social media data, please schedule a free demo today!

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