(Estimated Time to Read this Post = 5 Minutes)
In my last post, I explained a bit about CRM and how you could improve CRM by passing Web Analytics data into your CRM system. In this post, I am going to cover the reverse angle – passing CRM data into Web Analytics. Since most of you reading this are web analysts, I think you will find this post more relevant, but I think it is important to understand both sides.
Why Pass CRM Data into Web Analytics?
As I mentioned in my last post, we web analysts get lots of great information about website visitors, but for many companies (especially B2B), the richest data resides in the CRM (Customer Relationship Management) system. If you want to be relevant in your organization, it is always best to be as close as possible to the $$$ and that often means playing nicely with CRM systems. Don’t get me wrong, showing your CMO that you can lift form completion rates by 200% through optimization is awesome, but if you can show him the revenue impact of it right there in your Web Analytics tool, you will be a rock star! Additionally, I will show that if you don’t have actual revenue-generating events on your site (eCommerce and Media sites have this easy!), then not doing this could actually result in Web Analytics data causing incorrect business decisions…
Passing Post-Website Data from CRM to Web Analytics
OK. So there are many different ways to merge CRM and Web Analytics data including passing data from both into a massive Marketing data warehouse (or Omniture Insight), but just for the purposes of this post, I am going to assume that you are a SiteCatalyst person and want to get something done relatively quickly. In this scenario, we’ll assume the following:
- You want to see which of your website visitors completing lead forms on the site evolve into Leads, Opportunities and Revenue
- Your CMO has charged you with capturing all of the different marketing channels and asked for your opinion on where the company should invest to get the most Revenue
- You are tracking the various sources of traffic you receive and using SAINT Classifications to roll each up into a high-level marketing channel (SEO, SEM, E-mail, etc…)
Given all of this, you might have a SiteCatalyst report that looks like this:
As a web analyst, at this point, it looks like we might want to invest more in our E-mail program since that seems to be converting the best. Without CRM integration, that would probably be as far as we could go. But let’s now dig a little deeper. As I mentioned in the last post, when website visitors complete a form, we have a brief moment in time when we can connect our website data with our CRM data. Most CRM tools allow you to capture leads and set a unique ID for each form completion. At the same time, Omniture SiteCatalyst has a really cool feature (that many don’t use enough!) called Transaction ID. I highly recommend you read my full post on Transaction ID, but at a high level, it allows you to set an ID to a special SiteCatalyst variable and then days or weeks later, upload [normally offline] metrics into SiteCatalyst. The magic of Transaction ID is that when you upload these metrics later, they are tied to the eVar values (sorry – no sProps or Participation) that were present at the time the Transaction ID was set. That means that if a website visitor had a City eVar value of Chicago, a Traffic Source eVar value of Paid Search and a Visit Number eVar value of 3, then any offline metrics you import will also be tied to Chicago, Paid Search and Visit Number 3 in the respective eVar reports. This means that if you set the CRM ID associated with a website form completion, you now have a primary key (think Rosetta Stone!) that can connect your Web Analytics data to your CRM data!
So what does this mean to you? Following our preceding example, let’s assume that you have made this connection and later imported all of the new leads your CRM system has seen along with the status (i.e. Qualified) of each into SiteCatalyst (these new metrics would be Incrementor Events). This gives you a new metric named “Qualified Leads” that you can now see in SiteCatalyst reports and since you used Transaction ID, these imported CRM metrics are correctly attributed to all eVar reports in your implementation. The result is that you can now open a report similar to the one we saw above, but now it has “Qualified Leads” instead of Form Completes and a new Calculated Metric that divides these Qualified Leads by Visits:
The icons above the report show where each data point comes from and as you can see, the last column is truly magical in that it is combining data from two disparate systems (Cool huh?)! Once we have this, we can see that even though E-mail looked to be the best channel a few minutes ago, it now appears that SEM is where we want to spend our money. It turns out that E-mail generates form completions at the highest rate, but perhaps those form completions are all junk!
However, I like to go as far downstream as possible and nothing is better than cold, hard cash! Applying the same principles, we can import Qualified Opportunities, Potential Pipeline, but the CRM metric that trumps them all is Revenue. By uploading Revenue via Transaction ID, we can see how much $$ we got from each Lead Form completed on the website and tie it to any eVar value we have – in this case marketing channel/traffic source. The following report shows the result of this:
Again, we see that some data is coming from SiteCatalyst and some is coming from our CRM system. Our new Revenue/Visit Calculated Metric can be used to see that, in the end, it is really SEO that provides the most Revenue/Visit and maybe we should consider additional investment there. Please keep in mind that these examples are simply meant to illustrate the concept and show the value in adding CRM metrics to your Web Analytics tool. Finally, don’t forget that Transaction ID data is available in Omniture Discover so you can slice and dice this data even further there!
Targeting Based Upon CRM Data
Another really cool integration between CRM and Web Analytics is in the area of Test&Target. For those not familiar with Test&Target, it is an Omniture tool that lets you test and dynamically target content to website visitors based upon what you know about them. It is commonly used to optimize your website success metrics. However, this can be extended by importing in CRM data so that your targeting is based upon both online and offline data.
Let’s walk through an example. Imagine that a website visitor named Bill has been to your website a few times, looked at a few of your products and completed a lead form. Next, Bill spoke to your sales representative and is at “Stage 3” of the sales process (the discovery phase). Over the next few weeks, meetings take place and Bill comes to the website occasionally (your sales team would know when and exactly what he is doing if you read my last post!). But now let’s say that Bill is in sales “Stage 9” which is the final stage before the deal is won or lost. We know what products he wants, we know he is close to making a decision, we know how big is company is, etc… If we knew all of this, what would we want to show him the next time he arrives at our website? Here are a few things I would show to Bill on my home page when he (and only he) arrives on it:
- Case studies related to his industry
- ROI calculator for the product Bill is interested in
- Links to community content to show Bill that he would be well taken care of if he were to be a customer
- A time-sensitive offer (“Buy in the next 24 hours and get XX% off”) – You could even address him as “Bill” but that might freak him out!
- etc…
The point is that if you can get the rich customer data related to Bill and multiply this to all of your prospects, each one could see more personalized content that helps move them further down the sales funnel. You can even track how often they see these “recipes” and track the success of your intelligent targeting. If you are interested in this type of CRM-based targeting I suggest that you contact @brianthawkins who is a Test&Target Jedi-master…
Final Thoughts
Hopefully this sparks some ideas about ways in which you can enrich your Web Analytics data by adding CRM data to the mix. In the next post I will cover ways in which you can import CRM meta-data into your Web Analytics tool to augment your current web analyses.