5 Suggestions For Maximizing CRM User Adoption
CRM implementations have a higher failure rate than most other types of software. It is estimated that 50% of CRM implementations fail in the first three years. The cause of these failures is rarely hardware or software.
Most CRM failures are the result of a low adoption rate.
If your sales and service teams are not on board, they will either refuse to use your CRM system or avoid it whenever possible. Fortunately, it’s possible to achieve a high adoption rate by following a few guidelines:
The following are my top 5 focus areas to maximize user adoption:
WIIFM - What's in it for me?
Often, the directive to roll out a firm wide CRM comes from management. This can be a great benefit since a key to success is having management buy-in. However, it is important not to fall into the trap of building a system solely around what management hopes to gain. Management frequently wants visibility into the pipeline in order to forecast and any good CRM will deliver that. Do not forget about your day-to-day users. If your system is built only to support management and does not provide any benefits to the staff entering the information it will fail. My recommendation is to include staff level employees in your CRM implementation project from the beginning. You will want to make sure their pain points are addressed in your rollout. Here are a few things they may want:
- Workflow - Have the system do things automatically for them. Examples include automatic field updates when certain triggers occur. Automatic email reminders when it is time to initiate contact with an opportunity
- Reports on their own data
- Dashboards relative to the information they care about
- Real-time information about how they stack up against their colleagues
- Tools to help them sell/service i.e.: Competitive intelligence
- No duplication of input
Data Quality – A CRM is only as good as the data it contains. If your CRM has garbage data, your company will not use the system. Common problems include: Duplicate data, lack of data standardization, incomplete data and stale records.
- Duplicates – Duplicate data introduces several problems. In addition to creating confusion on which record is correct, you will have the issue of activities being logged to multiple records. This impedes the ability to get an accurate picture of the interactions with a specific contact or company and may introduce double counting. Additionally, when an update is needed, it is highly unlikely that a user will update all of the duplicates. For example, John Smith’s address has changed so a user updates the first John Smith record they find. The end result is multiple records for John Smith with different addresses. Will you know which one is correct?
- Data Standardization – This issue can be seen in many different fields but frequently in fields like state, name, phone number and industry. For an example, lets look at the state field; If your database contains New Jersey, NJ, N.J. and maybe even Jersey, you have an issue. Imagine the person tasked with producing a report of every contact in the state of New Jersey. Another common field example is Industry. Avoid an industry list that contains: Technology, Information Technology, IT, Tech, etc. Phone numbers that look like 212-555-1212, (212) 555-1212, +1 212-555-1212 and 2125551212 can be distracting especially when viewed in a report. How about first and last name fields containing lEWIS kOPP?
- Incomplete Data – Do you have a contact screen with 100 fields and only the first name and email address are populated? Consider implementing a scoring/rating system that indicates completeness of the data. An example of this is seen on LinkedIn; Your profile is 85% complete. There are also data enrichment services that can help populate your data and fill in some of the blanks. Finally, consider required fields but employ a strategy in leveraging this functionality. At a high level, you will only want to enforce a requirement if you are sure that the person entering would know this information at the time of entry. Some systems are capable of introducing additional required fields as a record matures in your system. For example, when an opportunity is first created the amount may not be known and should not be required, but by the time the stage of that opportunity moves to Quote, the amount field should be required. On the flipside, if you require a field and it really is unknown at the time of entry, you will be facilitating bad data. One client I worked with had an email address field as a requirement for several years. To their surprise we were able to show them thousands of records with variations of firstname.lastname@example.org or email@example.com. This is not only poor data but they were paying an email marketing company to send emails to these addresses.
- Stale Records – Old or stale data can be just as bad as incorrect data. I am frequently amazed when I look at customer data and find records that do not have an activity or a modification in over 5 years. Additionally, if you do email marketing and email a large number of inactive email addresses, your overall deliverability and spam reputation will be impacted. Most email marketing companies will suspend your account with as little as a 4% bounce rate. Pay attention to your email bounces. An email bounce usually means the person has left the company. Often, that contact in their new organization, is another opportunity for you to do business.
Complexity – There is a tendency to over engineer a CRM platform. Often, when working through an implementation, companies try to determine up front, every data element they might ever need to track and create a field for each. This results in large screens of data that are too complex to work with and may slow down system performance. At UTS, we built a proprietary application that reviews a CRM field by field and shows the percentage of utilization. Frequently we will find fields that are null on over 95% of the database. Fields like this are candidates for deletion. Similarly, picklists have a tendency to grow out of control. A good rule of thumb is a picklist should not have more than 30-50 choices.
Training – Invest in a training program at your organization. We complete each of our CRM implementations with an onsite training class. We recommend a training session of not more than 2 hours. If additional training beyond that is required it should be given as an additional class. Training should be done in the CRM you have customized for your organization. I would not recommend generic training on the platform as most organizations will have significantly tailored their application to meet their specific needs and it may look very different. In addition to initial training that is timed with your CRM rollout, you will need a solution for ongoing training and new employee training. I recommend short videos that can be hosted on YouTube or an internal Learning Management System. You might also consider an annual refresher program.
Accessibility – For many organizations, the main users of CRM are frequently on the road. It is important to select a system that is not only going to be available 24/7 but it should be available from any device and from any location. Users will want to access their CRM from work, home, their car, commuting and traveling. Many will access the CRM from desktops, laptops, mobile phones and tablets. Another benefit of mobile accessibility is having a contact’s information at your fingertips. Some more sophisticated systems are location-aware and will allow you to see other contacts that may be close by. Many times when meeting a new client, I will look into my CRM app on my phone to see what other clients we may have in the same building.
Having a CRM that is properly designed and implemented is key to its success. The tool then becomes invaluable and people often find themselves asking, “How did we conduct business in the past without it?”