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If you’re not sure how well your CRM system is being used, here are six ways to find out:
1. Look at usage stats
If people aren’t using the system, it’s not going to be adding any value, so a good starting point is to understand usage patterns. Most CRM applications will allow you to query the data to determine key usage statistics, such has how many records have been created or edited by a user, or when a user last logged in. Reviewing these usage patterns against a list of users that are expected to use the system will give you a very quick view on how well the system is being used.
2. Check what is it really being used for
List out the business processes that the system has been set up to support (for example, lead management, pipeline management, customer support, etc.) and review any associated documentation that describes how each process is managed in the system.
Armed with this information, ask users to describe how they use the system. This sort of assessment will determine if all the expected processes are indeed being managed within the system, flag where usage patterns fall outside documented procedures, and starts to identify where usage varies between individual users. There can be surprisingly large gaps between what organisations think their CRM’s are being used for and what they’re actually used for.
3. Is there friction?
Sitting down with users, and following a process through its path in the system, can often highlight ‘friction’ where things don’t flow smoothly, require excessive amounts of mouse clicks, or aren’t intuitive. Friction can have a big impact of usage patterns and productivity.
4. How well is it being used?
Take a sample of records from the system. Analyse that data in terms of the key supported processes. Are users updating the system in line with defined processes, or are there omissions and inconsistencies of use between different individuals?
5. Data quality
For key record types, form a view on what on what constitutes acceptable data quality for each step in the process. For example, if the system is being used to manage customer support issues, what fields are expected to be updated, at what level of quality, at each stage as the issue progresses from initial logging through to resolution. Now take a sample of records and score them as pass or fail against that quality standard.
6. How is reporting performed?
Identify the key system reports used by the business. Is the data they return complete and meaningful? For the processes supported by the system, look at how reporting data is compiled. Is it generated from the CRM system, from data derived from the system, or is reporting a standalone external activity? Reporting can be one of the biggest indicators of a system’s health. If users don’t trust the data for reporting purposes, then it’s generally a sign of significant usage issues.
The results of this sort of analysis can be quite eye-opening. The good news is that most issues can generally be fixed – the key is to understand if there’s a problem in the first place.
Richard Boardman is founder of Mareeba CRM Consulting.
1. Look at usage stats
If people aren’t using the system, it’s not going to be adding any value, so a good starting point is to understand usage patterns. Most CRM applications will allow you to query the data to determine key usage statistics, such has how many records have been created or edited by a user, or when a user last logged in. Reviewing these usage patterns against a list of users that are expected to use the system will give you a very quick view on how well the system is being used.
2. Check what is it really being used for
List out the business processes that the system has been set up to support (for example, lead management, pipeline management, customer support, etc.) and review any associated documentation that describes how each process is managed in the system.
Armed with this information, ask users to describe how they use the system. This sort of assessment will determine if all the expected processes are indeed being managed within the system, flag where usage patterns fall outside documented procedures, and starts to identify where usage varies between individual users. There can be surprisingly large gaps between what organisations think their CRM’s are being used for and what they’re actually used for.
3. Is there friction?
Sitting down with users, and following a process through its path in the system, can often highlight ‘friction’ where things don’t flow smoothly, require excessive amounts of mouse clicks, or aren’t intuitive. Friction can have a big impact of usage patterns and productivity.
4. How well is it being used?
Take a sample of records from the system. Analyse that data in terms of the key supported processes. Are users updating the system in line with defined processes, or are there omissions and inconsistencies of use between different individuals?
5. Data quality
For key record types, form a view on what on what constitutes acceptable data quality for each step in the process. For example, if the system is being used to manage customer support issues, what fields are expected to be updated, at what level of quality, at each stage as the issue progresses from initial logging through to resolution. Now take a sample of records and score them as pass or fail against that quality standard.
6. How is reporting performed?
Identify the key system reports used by the business. Is the data they return complete and meaningful? For the processes supported by the system, look at how reporting data is compiled. Is it generated from the CRM system, from data derived from the system, or is reporting a standalone external activity? Reporting can be one of the biggest indicators of a system’s health. If users don’t trust the data for reporting purposes, then it’s generally a sign of significant usage issues.
The results of this sort of analysis can be quite eye-opening. The good news is that most issues can generally be fixed – the key is to understand if there’s a problem in the first place.
Richard Boardman is founder of Mareeba CRM Consulting.
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