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Keen Footwear Leveraged Web Analytics Tool To Increase Its Active Users Social Media Platform By 213%

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keenAbout Keen Footwear:  KEEN is a fast-growing shoe making company based in Portland, Oregon which produces casual shoes for all types of outdoor activities. In today’s world, we live a very hectic and busy life, then get relax, play in-between and then resume the weekly dose back again. At keen this kind of life is termed as Hybrid Life. Thus, the mantra of KEEN is to innovate and design products like footwear, bags and socks in such a way that allows you to transit from business practices to play ground without ceiling, and with maximum comfort.

Keen Footwear’s Business Objective: KEEN’s business objective was not a different from other shoe manufacturing industry who were having online presence. KEEN was already a established brand with loyal and strong customer portal/group. But then the company needed an effective solution for their presence in social media which can help them fetch more and more loyal customer. They had a web analytics in place, only requirement was how to analyse and understand all of its metrics and traffic trend so that a solution can be garnered which will give them meaningful insight.

Approach / Strategy Adopted By Keen Footwear: First and foremost they hired a Web Analytics consultant SwellPath who can help them to build a framework around their social media campaigns. Thus KEEN with the help of SwellPath identified and created a check list termed as bucket of metrics including following highlights:

  1. Authorship: This is nothing but how many final conversion a company is making.
  2. Growth: How many people have themselves chosen to receive company’s promotional and marketing messages?
  3. Reach: The content got reached to how many people.
  4. Engagement: How many users are active on company’s site?
  5. Influence: An ability of company’s content to make people more attracted towards them.
  6. Sentiment: The normal chit chatting, commenting and feeling people are sharing through social media about them.
  7. Effect: It’s a measure that how social media, website conversion, in-store sells and all above check list leads them to achieve that position where they stand now.

With the help of this, they effectively used a KPI framework to determine metrics best suits for KPIs. On the same basis, following questions are formulated to work upon it:

  • What can be inferred from each metrics?
  • Which metrics fits best to my goals achievement?
  • What is the reason behind movement of metrics from positive or negative direction?
  • How should we analyse it as a social media marketer?

Result Achieved By Keen Footwear: By logically doing such activity of placing various metrics into buckets, KEEN was able to concentrate upon their posting style, content and advertising strategy align with their business objectives. Over a 10 months only they had observed a fantastic growth curve. And the results are as follows:

Facebook Twitter
92% increase in Page likes. 110% increase in Followers
342% increase in Post Reach. 49% increase in Retweets
137% increase in Post Engagement 16% increase in Mentions
117% increase in avg. Interactions per post 62% increment in avg. Interaction per tweet
213% increase in Active Users 90% consistent & positive Sentiment Ratio

KEEN is now able to compete hand in hand with other juggernauts in social media campaigning and can offer its customers with an innovative product base & better engagement.

Learning: As a result of buckets recognition, allowed KEEN to sort out individual KPIs and set concrete goals according to it to align all web analytics strategies within calculated boundaries of those goals. Increase in performance metrics has helped KEEN to gain good level of sophistication on social media platform. By identifying KPIs from within key metrics, the process of social analysis became focused & ad hoc tests generated and misguided steps could be eliminated. Goals with benchmarks were set with those of KPIs and metrics.

  • web-analytics


  • There are 2 comments


    • 3 years ago

      Nikhita Reddy   /   Reply

      Good and neat post. The results were also explained in a clear manner. This case study shows the power of web analytics.

    • 3 years ago

      Indrajit Goswami   /   Reply

      Good post. Only limitation is with the ‘objective’ portion. It is always better to write objectives as expected targets in concrete language. We must avoid writing problems there.

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