Feeling overwhelmed by social media monitoring? If so, you’re not alone.
Thanks to relentless updates and countless ways to pull information, it’s no wonder that data extraction and analysis is an anxiety-provoking process. When you throw in fear of making data mistakes, it can almost be too much to handle. But we’ve got you covered.
It seems that for many marketers, collecting and dissecting qualitative and quantitative data is a bigger struggle than we’d like others to think. It’s unfortunate too, because there’s a wealth of information waiting out there, available to help refine your digital marketing strategy. If this rings true for you, you may suffer from these three common (yet fixable!) user-error data mistakes.
Data Mistake #1: Analyzing Without a Plan
While most know data analysis is a critical component of any campaign, sometimes marketers jump right in without a plan. That’s a surefire way to feel really lost, really fast.
In fact, in a recent study interviewing 600+ people, 85% admitted that they are unable to fully utilize data. I’ll bet it’s because many of them have no clue what they’re looking for, and definitely do not understand how the data can and should inform next steps.
A Better Choice
Instead of blindly monitoring out of obligation, be thoughtful about your research. Before scrolling, consider your long-term goals and specifically look for data points to support those objectives.
Data-driven decisions are the best kind of decisions because they remove opinion from the equation. For content and engagement planning purposes, as well as proving ROI, data is on your side.
- Educate your boss
- Data is particularly helpful when you’re trying to demonstrate the success of your social media campaigns. For example, if your boss sees a couple of likes and shares on a competitor’s post, he or she may be completely convinced that the competitor has a better social media presence than your brand.
- Save your job (and your sanity) by using the data to defend your hard work. Show him or her that while that single post may have earned some attention, your brand has more followers and engagement on the platforms that matter more to your target audience. You might even want to walk them through your chosen tool, showing and telling about your impressive engagement results.
- Create the right content
- Since content marketing generates over three times as many leads as outbound marketing and costs 62% less, what you say, how you say it, and who you say it to is paramount to campaign success.
- If you have a new content campaign in mind but don’t want to invest the time and resources to create it yet if you’re unsure it will be successful, turn to the data: a quick scan of what’s worked well (and what hasn’t) for both you and your competitors in the past will help you make an educated guess about whether or not to proceed.
- If you do decide to proceed, take notes about what performs best. Identify tone of voice, content type, channels, ads, and commonly used hashtags and incorporate these best practices as you produce your own campaign.
- Find influential voices
- If one of your goals is to connect with industry power players (as it should be), use the Discover feature in your Rival IQ account to reveal a list of the top accounts sharing relevant content.
- From there, dive deep into their social media channels to see who they regularly interact with and the nature of their conversations. You can see what they talk about, review common hashtags and keywords, and observe typical questions and requests. These insights will shape the way you compose your social media posts, and also provides you an opportunity to respond to and share influencer content where appropriate.
Data Mistake #2: Turning on autopilot (and not looking back)
It starts with high hopes as you set up an analytics profile. After spending a couple of fun hours brainstorming and creating keyword query combinations, you sit back in amazement as the results start to roll in.
At that point however, the novelty begins to wear off. It’s definitely tempting to close the analytics tab and turn your attention to other aspects of your job… or hilarious memes that just really get you.
While automation is all fine and good, the cons begin to outweigh the pros if you set up a comprehensive monitoring account and then seldom look at it. Data analysis is most effective if a human being is regularly monitoring, tweaking keywords, and evaluating performance along the way. Gathering these insights is a best practice to inform strategy and content creation. If you just leave it running in the background, the entire exercise becomes pointless.
A Better Choice
Avoid this common data mistake by sending automated alerts to your email instead. You can still stay on top of the results without having to log in to your account multiple times a day.
Here are some examples of the alerts you can customize and opt to have automatically pushed to your inbox.
- Likely boosted post detection
- Instagram bio link detection
- Sessions increase for landing page
- Sessions increase from source/medium
- Big increase in search ranking for top keywords
Data Mistake #3: Failing to create actionable insights
Data analysis is only helpful when you take action. You can run numbers and analyze conversations until you’re blue in the face, but doing so without implementing changes based on insights falls into the “data mistake” category every time.
When I worked at a PR agency, we regularly produced reports for clients. A common response from the C-Suite was: “Okay, so what do these numbers mean and what are we supposed to do with this information?”
That’s where actionable insights enter the picture. In a nutshell, it means using the information gleaned from monitoring and analysis to make better and more informed content and engagement decisions.
A Better Choice
Whether you’re sharing reports with a client or your internal team, be sure to pair every data point with context and recommendations. Take Samsung, for example. Samsung took notice when their social listening tools revealed customers shared pictures of their TVs playing specific shows, like HBO’s popular Game of Thrones. Previously, Samsung was sharing inspirational imagery that didn’t quite connect with how people were using the product in real life (the brand depicted pristine rooms with turned-off, wall-mounted TVs, whereas user-generated content featured TVs on stands with a beer in the foreground).
Samsung didn’t just file this information away: they used it to make meaningful changes to their marketing campaign. Now that they had a better idea of how people wanted to interact with their products, they began incorporating more realistic imagery. The result? Content that resonated better with target audiences and higher brand engagement.
Be the hero of your next digital marketing meeting by bringing new ideas to the table that are rooted in data.
Are you a victim of any of these common user-error data mistakes? Send us a tweet and let us know how you plan to make adjustments to your social listening strategy this year.