Photo cred: Kevin Dooley

This is the second post in the mini-series: Introducing Numbers to the Community.

The social data revolution has brought us more data than ever before, and communities can take advantage of data silos to create a brilliantly tailored experience for members.

In part 1 of this series, we talked about the basics.

• The first step is to think about your community and its goals—because that will have a huge influence on the type of metrics you’ll need to collect.
• Second, data by itself is lonely, so we talked about the need to bring your community data (from somewhere like WordPress) and put it into the mix with your other social media data.
• Finally, the frequency of updating your data will determine how specific and sensitive your data will be. The more frequently you collect data (weekly vs. monthly, for example), the more targeted your data will be.

Now we’re going to start making the metrics work for you and your community. One of the biggest disappointments I see is watching good data go to waste. So let’s take those metrics and make your community brilliant.
(See part 1 for more details on the first three steps.)

4. Context is Crucial

Data always starts with a context. Ever hear phrases like “Double digit growth” and “The price has gone up 200%”? Neither of those mean much without context. What this means for a community is that when you look over your metrics and see something changing, you’ll need to put it in context to really understand what’s going on.

A good example might be the case where a community makes great strides growing its membership for the first 12 months. Things are going great, you’re tracking metrics and smiling as the community starts to take shape. But in month 13, your numbers drop. Membership is down. In month 14, same thing. Is it a trend? Month 15 and the membership decreases again. At face value, this is a little alarming. But as you look down the metrics sheet, what you find is that you’re still adding new members. And while the number of conversations created each week is the same, the average engagement under each conversation is up. Oh, and the time spent logged in by the average user per day is going up.

In this example, the number of members leaving is slightly higher than the number of new members arriving at the community, but (and this is a big but that can be overlooked when numbers start to decline) the context looks really positive. The community is more engaged. The amount of time on the site is looking really good and increasing. What might be happening here is that the quality of the community is increasing and, although a few of the early sign ups are leaving, the overall health of the community is actually doing better. Those members leaving might just be people who came to the site and didn’t have time or realized it wasn’t the right community for them.

Remembering the context as you look across your weekly or monthly metrics will help you look for deeper insights and meanings behind the data. Not only will that help your blood pressure (stay calm, stay calm) if you see decreasing numbers, it will also help you think holistically about how your overall community is working.

5. Look for Overall Movement and Compare Apples to Apples

Linked tightly with context is the idea that you need to be looking at the data over time and as a “movement. What we mean here is that there will be spikes and down times and roller coaster rides—all of which is a natural part of how we work. Take retail – there are huge peaks around the holiday seasons, sale seasons and so forth, but there are also times when tumble weeds blow through shopping centers because people are at home saving their money. It’s cyclical and your community metrics may be, too.

For example, if you have a job-search related community,  you might see peaks around January when the new year is underway and it’s widely understood that people start searching for a new job. If you have a knitting community, you might see spikes leading up to winter.

In these instances, where the pattern is based on time of year, you’ll want to compare apples to apples to look for “like-movements.” So look at comparing January this year to January last year and the year before. Is the general movement positive? Is it the same or better than last January? Often government statistics will compare quarter on quarter from the previous year because so much of buying behavior (and general human action) is based on cycles.

6. Get Comfortable With Long Term Data Collection

This might sound a little overwhelming or daunting, but a long-term data outlook can really provide ongoing benefits to your community. Businesses that look to short-term data often miss movements and the context to help them really understand what the metrics are saying.

A long-term outlook, integrated with general community administration and planning, is one of the best tools to ensure your community continues to grow and maintain a healthy level of activity. Some forward-thinking organizations invest in research tools like trackers. These may not change much from week to week but provide really beneficial insights into long-term changes in the market—giving these companies the ability to react whatever the situation.

Communities can benefit from much of the same insights whether you track 5 metrics or 50 metrics. Daily, weekly or monthly , no matter how you measure your community, understanding that it’s a long-term investment will help you provide the community support that will ensure the community continues to do well.

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Hopefully these tips will help you start to look at your metrics, take value and start to understand what insights you can get from your community data. Investing the time in data collection has the potential to reap huge benefits for your community, just like it has for many businesses that see data and analysis as an investment in the long term health of their customer base.

This is Part 2 in a 3-part series that hopes to provide a basic introduction to collecting data on a community. The goal is to give community managers the confidence to make data collection and basic analysis an important part of their toolset in creating the best possible community.

Look for Part 3 next week, covering some tricks, insider advice on community data and why understanding data now will help community managers for years to come.

Chris Dowsett

Chris Dowsett (or Dows for short) is your friendly data analyst, statistician and numbers person. Originally from Australia, Chris works for Intuit as a social media analytics manager. He’s also studying a Doctorate focused on improving data use in business decision making.