Common Errors To Avoid While Conducting Social Media Analytics

Common Errors To Avoid While Conducting Social Media Analytics

You spent a significant time on data analysis only to realize that your initial approach was incorrect. This creates a lot of frustration, and plenty of missed opportunities that your competitors will be grateful for!

Obviously, trial and error are both typical of analysis. When you blend and manipulate data you can sometimes miss the right path. Check the different kinds of mistakes marketers make while performing analysis, which can be avoided. There are plenty of learnings here for any type of business – from a bank to a bicycle retailer!

Avoid these marketing analytic mistakes which can be misleading

Avoid assuming low numbers are bad

Low numbers in marketing analysis may seem a topic of concern, but avoid being fooled. Low numbers do not always mean bad performance.

There are specific metrics, where the low numbers actually are positive. For example, if your email has decreasing unsubscribe rate then it indicates your audience finds its content appealing. If your consumer acquisition cost decreases, it means your marketing hard work is being rewarded. Never assume that low number defines unsuccessful for your team.

Sometimes low numbers can highlight an unresponsive marketing channel. This means you need to concentrate and invest on other marketing campaigns. For example, your social media analytics displays good numbers of followers on Facebook, Twitter, and Linkedln, but conversation rates look low.

If your social media goal is to increase conversion rates then check, which social networking site is most ineffective? Suppose your Facebook displays 0.20% more conversion rate than Twitter means you get a marketing opportunity to reinvest on Facebook rather than Twitter.

Avoid blunder between correlation and cause

Sometimes, two metrics will be seen increasing or decreasing, simultaneously and that too at the same pace. You may assume that these metric progressing together are directly correlated.

Shockingly, these metrics were entirely unrelated causing a blunder. If you are in such a situation where two metric increase or decrease, simultaneously then dig further, but don’t assume blindly.

Avoid confusion between visits and views

Visits and views sound similar but vary a lot. ‘Visit’ means a visitor coming to your site from some other URL. ‘Pageview’ or ‘view’ gets counted, when page loads and reloads on a browser. For example, if someone browses through five pages on your website, before leaving then it is counted as one visit but 5 views.

Avoid misunderstanding between leads and MQLs

‘Lead’ means anyone filling and submitting forms on your landing pages. ‘MQL or marketing qualified lead’ is judged as potential consumer on the basis your company’s definition of MQL.

Both lead and MQL needs to be kept separate because marketing channels and content used by company team to nurture the former may differ than what they employ to foster MQL.

For example, lead may be given a lot of educational material and some preliminary company information, whereas MQL may be supplied with information on how the product/service you offer communicates with their interest.

Biggest error marketers make is not drawing out the actionable takeaways from their data. Readjust your efforts, as soon as you find out that a specific marketing channel is ineffective. Switching gears, when you drive a social media campaign is always encouraged

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