Month: October 2014

How to avoid the common pitfalls of a CRM project [part 3]

I was going to write a lengthy piece about the importance of Data in relation to any CRM programme, and this post may well  turn out to be longer than I wish, however, there is really only one thing you need to remember…

Data is going to take much, much longer than you anticipate.

Unless your CRM application is only going to take data from one data source, and that data is clean and very well understood, then it’s going to take a huge amount of effort to handle.

Actually, even if you think your CRM application is only going to take data from one data source, and you believe that the data is clean and very well understood, then it is still probably going to take a huge amount of effort to handle.

If you only take away the message that “data is going to be a big part of your CRM programme” then you’ll be better off than most.  But if you’d like a bit more information about Data and CRM then please read on…

Any CRM solution is only as useful as the content it contains; the data.  Data is the lifeblood of your CRM solution as it is the means by which users are informed about the customer, so they can best direct their decisions and actions to meet business goals.  The content of a CRM solution is as important as the people, processes and technology

There are a handful of data-related topics that a successful CRM programme should consider:

  • CRM data model
  • Master data management
  • Migration of data from decommissioned applications
  • Integration data from the IT estate
  • Reference data and data subscription services
  • Management Information

The CRM data model

“We want a single view of the customer” is often mentioned at the start of a CRM programme, but do we really know what we mean by “Single View”?  Do you know what it should contain?

It is important to get a early view of the content you are likely to need within your CRM, to find out the data you need to support decision making along various customer journeys; and just because you can get access to a particular data item it doesn’t mean that it should necessarily be in your CRM solution.  Indeed if the data doesn’t add to the value of the customer experience then its presence could well undermine it by adding to the burden of data maintenance and making screens  overly complex.

Get an early, “top-down” view of the content that need to be in your CRM.  As well as obviously things like contact details and preferences you will need to consider if CRM should contain service requests, complaints, quotes, purchases, as well as correspondence history and documents, etc.

If any entity (category of data) or attribute (individual data item) isn’t necessary for your customer journeys then don’t include it.  And those that are needed for several customer journeys are therefore all the more valuable to your business, and therefore need to be well maintained. Understanding the value of data is a great start for your CRM programme.

Whilst we’re on the subject of data maintenance it’s important to consider those attributes that are mandatory in your CRM application.  My experience suggests that mandatory fields are often more bother than they’re worth.  It is often assumed that simply by making a field mandatory that we can ensure we get the information we require, however this can be the opposite of what we actually get.  Be careful where you demand data from the users of your CRM application, if the field is mandatory and they’re not sure what to enter, then there’s a good chance that you’ll end up with them either guessing a value or, even worse, picking some default.  It’s better to have an empty field, which can show you your unknowns, than to have a complete field where you don’t know if the value is correct or not.

Master Data Management

It’s unlikely that your CRM solution will instinctively know how to best match customer records across your IT estate, so you will need to consider how best to match data to create a “golden record”. Whilst it is important to minimize the number of duplicate records in your CRM solution, it is even more important to ensure that you don’t incorrectly match records that belong to different people.  This is particularly true if your CRM solution is the master for an individual’s or organization’s financial transactions.

My top tip is to consider matching strategies early in your CRM programme, and start testing their outcomes against production data as soon as possible.

Migration of data from decommissioned applications

Legacy systems are never as well understood or documented as they need to be; and when it comes to migrating historical data who knows what value “X” meant on that lookup table from 8 years ago.  Yes, you will have to involve IT but you will also need to work with the business users experienced in using that legacy application every day.

My last tip here is to start data quality analysis early in the programme too, and if at all possible look to clean data in-situ before any migration.

Integration data from the IT estate
Hopefully the IT estate you’re going to keep is better documented, but just like those legacy apps there will be areas where they are not well understood.

Reference data and data subscription services

As well as the data from your existing applications there are a many great data sources available for a subscription, freely available from the OpenData community, or increasingly from social media platforms.  These can be used to enhance the understanding of your customers, and provide additional matching strategies too.

Management Information

We started by talking about understanding the value of data, knowing where it is used to inform decision making within customer journeys.   But data can also be used collectively within Management Information (MI) reports.  Make sure that the data within your CRM solution not only supports individual customer journeys but is also sufficient to generate relevant MI reports too.

At the end of the data, when all’s said and done…

Data is the lifeblood of your CRM solution,  the means by which users are informed about the customer, so they can best direct their decisions and actions to meet business goals.

The flipside to this is that some users will blame the data in CRM to avoid using the application and adopting a CRM way of working.  The data in your existing IT estate may have been wrong all along, but in a product-centric view people may not have been exposed to the bad data they now see in your CRM application.

If you get your CRM data right, users will flock to it as it will be a valuable resource to help them.

I could have written lots more on this topic and will revisit it in the future.  If you want to know more drop me a line or comment below.