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How to calculate 'Member Spend' within a Community

Khoros Oracle

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In this latest article about quantifying Community Value, I want to examine the methodology for measuring ‘Spend’ as a business value lever within Online Communities.  ‘Spend’ is the value lever that always gets the most attention from a brand’s leadership when the story is conveyed effectively to them.  Yes, it is true that ‘Savings’ (another one of the 4 S’s) is the value lever that everybody seems to talk about, but ‘Savings’ seems to be afforded the majority of attention not only because it is a common objective, but because it is easy to calculate as well.  But believe me when I tell you;  if a brand has an Online Community, the very top of their leadership organization cares about this:

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What I have also found to be true is that although the formulas for discovering the different variations around Online Community member spending are extremely simple, the actual technical and/or technological tracking to prove the ‘spend story’ can be difficult to achieve.

Let us first start with the primal formulas that are used to examine Community Member spend.  You basically need two averages to compare in order to conclude that a Community member is spending more than a non-Community member:

  1. The average of a regular (non-community member) customer spending with the brand.  Hopefully, the business is mature enough to have this data on hand at all times, but sometimes (depending on where one sits in the organization) it can be a bit difficult to track down this data
  1. The average spend of all community members (preferably those who logged in during the last year) with the brand

It is likely that community-member spend will be higher than the average non-member ...though not always. It is, indeed, very rare when that is not the case.  Let us look a bit more closely at how we slice and dice the data in order to discover the truth of whether Community Members spend more or not. 

First, reconciling these averages can sometimes be arduous if you do not have the right technology experience and tools to handle large data sets (SQL, Tableau, etc).  Second, it is also very dependent on the brand having Single Sign-On (SSO) in their community in order to even have the data..  If SSO is not set up, then this measurement exercise is nearly impossible.  

But do not give up hope.  It is possible for a brand's Marketing team to check where people are 'coming from' when a customer placed items in their shopping cart and/or successfully completed an order.  If the origins of the shopping experience (from what the brand can tell in their tracking data) come from the Community, then the Community team should know about it!  Ideally, Web Marketing (or Web Sales) should also know how many online conversions had Community in the purchase journey.  Here are three ways to track conversion events coming out of Community:

  1. The most common way is if the Community is directly integrated into the CRM system of the brand.  If that connection is all wired up, you can usually tell which Community users made purchases using the brand’s online shopping cart after they spend some time on the Community.  However, a CRM integration may not tell you definitively what content was read in the community by the purchaser, and precisely when the person read the purchase-inspiring content.   A CRM integration with Community will advise you (by virtue of the member lists) that Community members spend more (or less) than average non-Community members.  It does not necessarily indicate what content was digested in order to influence a purchase decision
  2. Another less common way to track DIRECT conversions is to have an integrated shopping feature (with products!) within the Community.  With that sort of feature/integration enabled, you can definitely track conversions very tightly from the Community
  3. The easiest and most standard way of looking at Conversion events as a result of Community is just tracking cookies/sessions as a Visitor moves from the Community onto a product page, and subsequently converts.  Many product pages of e-commerce sites are able to read where a Visitor (and ultimately, somebody that 'converts') came from.  If where they came from is the Community, then great, let the Community get some credit!

Lastly, and I will not include the following in the numbered list above because the following tactic does not involve any direct interaction with one’s own technology or specific data points, is to make some assumptions using formulas.  I am loathe to do this when calculating Spend if the Community is already live and successful (because I would rather endeavor to get the real data instead!), but sometimes there are exceptions.  Here are some studies that have assisted me when using assumptions:

And an additional reference point that I use not only when assumptions are necessary, but also as a ‘gut-check’ when I have made calculations using the actual brand’s data is our own Millward Brown Digital 2014 study on the impact of Marketing & Sales.

All in all, calculating the monetary yield of Sales from Community can be tricky, but it is only tricky due to a lack of a fully wired-up tech ecosystem.  But once the story is told, people really do take notice.  The Community will begin to gain a new level of credibility and respectability within an organization.  Make it happen if you can!   

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How to calculate 'Cost Savings' within a Community 

2 Comments
Trusted Contributor

Hi! The links in the bottom in this article tells me I don't have permissions to view it. Could you please help?

Khoros Staff

@HelgaMarieAuran I could not find a reason you would be unable to access, it is a link to a public post, can you access it from this link