Analytics does not always mean predictive models. Sometimes a simple dashboard tracking your team’s progress is enough to spur excitement and encourage a team to perform. Oftentimes, charting a metric implicitly sets performance targets by encouraging people to be better than the days or weeks before.
To illustrate the power of charting a simple metric, see the graph below. This shows the growth in social media referrals to a corporate website. In this case, Day Zero represents the first day of charting. The social media team tracked the data daily, and simply plotted it with the goal of improving the number of social media referrals relative to the day before. For example, if there were 1,000 referrals yesterday, then today’s goal is at least 1,001.
Every day, the data was updated and analyzed. Days with particularly surprising results, such as a dip in referrals or a dramatic increase, would lead to a set of e-mails or a meeting to discuss the situation. This led to the team tracking tactics around increasing referrals, and migitation projects to avoid drops in referral traffic. Using such an approach, we were able to increase social media referrals by 50% within two months. This is equivalent to thousands of dollars in cost-per-click ads.
The growth rate, as illustrated by the graph, was linear. It was also sticky: even without new initiatives or special campaigns, the growing social user base was more willing to visit the company’s website and respond to regular blog posts, Facebook messages, and Twitter tweets.
How do you get such great results quickly and easily? Below are the tactics we use to drive improvements.
- Track daily. Never stop. Make tracking the dashboard a habit. If possible, start with a manual approach to force yourself or your team to reflect on the numbers. Nothing sets a performance-enhancing habit better than ensuring you’re constantly thinking about important metrics.
- Make dashboards visual, and share them with the entire team. Encourage and remind employees to check dashboards regularly, and bring them up in meetings. Share them widely and celebrates successes publicly across the organization. Solicit feedback when sharing with the team.
- Have daily meetings to review progress. These meetings should be short, with a goal of analyzing success around metric improvement, or discussing ways to mitigate poor performance. Keeping meetings to fiften minutes is often enough, and enables the team to celebrate and reflect daily.
There are a few risks with such a dashboarding approach, so make sure you keep these in mind.
- Allow short-term performance hits for long-term performance gains. Performance hits will come with experiments, but experiments also enable you to see which tactics work best and as such, which ones should be scaled. In the graph above, the second month had more variability then the first, and part of the reason for this was the number of experiments that were organized. Scale the successful experiments, and quickly stop the underperforming ones.
- Make small performance drops an expectation (and don’t panic). Every metric has some variability, so expect days where you will do worse than the day before. Ensure that the team isn’t punished or discouraged due to small, short-term drops in performance. Panic only when when results are consistently worse than the day before.
- Optimization assumes there is something to optimize. Most importantly, optimization assumes you already have a base of supporters, customers, or fans. Meaningful improvements from analytics only result from optimizing on an existing base. For example: growing 5% a day on an initial base of 10,000 users will lead to over 40,000 in 30 days. On the other hand 5% growth on 100 will yield similar growth rates, but your base won’t hit critical mass.
Simple metric measurement is a powerful first step to any analytics strategy. By measuring progress daily and promoting a culture of regular performance improvements, your teams will already see better and more improved results. This will also prepare you for more advanced analytics projects.
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