“Data is the LIFE BLOOD of a CRM System.
The QUALITY of the data directly relates to the overall HEALTH of the system.” – Rowland Dexter, Managing Director, QGate
Data Factor: Why is data so important?
Data is unquestionably the lifeblood of a CRM system. If your data is unhealthy, your CRM will definitely suffer. Unfortunately, data can be expensive. Certainly in the first phase of a CRM where if you’re going to do any data work it’s going to be the most expensive, time-consuming part of that phase.
Where do you have data today? Outlook? Excel? Maybe in Legacy Systems and around the organisation?
One of the common aims of CRM is to consolidate and centralise information. Sounds simple, but in real terms this means extra processes that take time such as:
- Pulling data out of all current systems,
- Reformatting data
- Importing data into new system
- Data cleansing considerations: deduplication, address verification etc.
The costs of all of these processes can be considerable and are often underestimated. However, the cost of not considering this area seriously will be even greater.
Poor quality data is one of the most common causes of low user adoption. Your system could be the best solution around with user-friendly, intuitive functionality, but if the data is not current, correct and duplicate free then the users will see that very quickly. As confidence in the system drops, users take less care in the data they enter, and the situation spirals out of control. In the end, users stop using it and implement their own systems, usually spreadsheets that they feel they can rely on.
Inaccurate, duplicate, out of date data also leads to low confidence in the output from CRM particularly around marketing, forecasts, reporting, customer service etc.
You must consider data from the start of your project very, very important.
Initial Data Load
Where is your initial data coming from? Could be a previous CRM system, or could be a number of data sources including Outlook contacts lists, ERP system, separate mailing lists, to name a few.
The layout, names of the data fields, the format of the data, even how the data is represented will be different for each data source. None of these will have much if any similarity to the layout, format, etc. to the CRM database you plan to put the data onto.
Let’s consider a quick example – address format
If you used a spreadsheet to look at the data, how many columns are used to hold the address? Are the column names the same for each source? Your target CRM system will most likely have a separate field (column) for each element of the address. Consider also if your data sources have more than one address for a company and/or contact.
Is the format of the addresses consistent? For example, is the town or city always in the same place?
It is not uncommon for us to see in a tender document the requirement for “a simple import process.” Based on the above it is clear that this is a clear indication that the data factor is not fully understood.
So when considering the initial loading of data there is already quite a challenge.
You will see a lot of talk about Data Quality. There are many companies offering to assist you with this topic. You may do well to engage with one or more of them, but before you do, consider what you mean by Data Quality. Listed below are some specific areas to consider:
- Duplicate data
- Valid data – addresses, emails, phone numbers
- Currency of data – is the data up to date, is the data still relevant to your business
- Profiling and enrichment – the process of adding additional data to a name and address to make it possible to segment your data for marketing and reporting processes
- Integration – linking systems to pass data between them to improve process efficiency
Bring on the Data Custodian.
This is about setting out your Data Standards in terms of, data entry standards, security (who can see what), how it is maintained.
Referring back to the opening statement, data is the lifeblood of CRM, it needs to be kept healthy, it needs a health check and it will need looking after.
Setting out your standards and implementing monitoring and controls, helps to maintain the quality and health of the data. Simple things like ensuring data entry is managed wherever possible via defined pick lists all aid Data Quality. When we start talking about this in projects, a common request is to make lots of fields mandatory. A reasonable request on the face of it, but what happens if at the point in time of adding the records the user simply does not know what to enter. What do they do…? Lie? Well, they might have to if they are to progress what they are doing. Use mandatory fields sparingly, but have checks in place to highlight those key fields in your CRM that still require entry, this is normally simple to achieve using a lookup/query with the system and making this available to the Data Custodian or the users themselves.
There are a number of data providers that are able to offer point of entry validation for addresses and other data, Loqate is one of our favourites. Obviously managing the Data Quality at a point is generally much more cost effective. Prevention is better than a cure.
The next post in this series is about what to look for in a CRM partner. To read it, please click here.