Does this scenario sound familiar to you? You've invested in a brand new Salesforce implementation, created training programs and built enablement activities. You look at your adoption statistics and see that despite all your best efforts, only a small portion of your users actually use Salesforce. You scratch your head trying to understand not only how to increase Salesforce usage, but also how to realize high value from it.

There are many different ways to increase Salesforce adoption. Some customers focus on training activities, while others focus on leadership communications. Whatever the method, at the end of the day, the objective is to create user behavior that realizes the full value of Salesforce.

Instead of looking at tactical change management activities, let's take a look at the strategy of changing user behavior. It typically has three main stages:

The Power of Data

There are many ways to understand how users behave on Salesforce. For example, you can send out a survey or solicit feedback from a focus group. However, those methods would only  give you the perspective of a very small percentage of your user population. A better solution is to use the data users generate in the system to understand what they do and why they do it. One way of doing this is by using cluster analysis.

When users perform actions in Salesforce, they generate data. For example, in Sales Cloud users generate opportunities and Chatter posts; in Service Cloud they generate cases and approval records. With cluster analysis, you can use this data to group your users into personas with similar behaviors (as opposed to similar characteristics, like geography) and potentially similar values (e.g. “I believe in collaboration” or “I like winning”).

In Salesforce, like in real life, it is a lot easier to encourage a certain behavior in a group of people with similar values, than in a group of people without much in common. Therefore, once you identify those groups and their values (i.e. user personas), you will be able to create targeted campaigns to change the group's behavior.

Changing User Behavior

Cluster analysis is part science, part art. To best illustrate the process, let’s take a look at how we used cluster analysis on one of Salesforce’s largest Sales Cloud customers:

1. The science:

• Data collection: For each user, we collected many quantitative data points related to their Sales Cloud activity (e.g. total number of opportunities, average win rate, login frequency, total Chatter posts, etc.)
• Analysis: We used a data mining tool to split the user population into groups to which we’ll assign personas. For more information on one of the tools available to perform this grouping exercise (AKA cluster analysis), check out this link.

2. The art:

• Personas: Based on the groups provided by the data mining tool, we identified the different personas who use Sales Cloud. For example, we found that a certain group of users had an exceptionally high win rate, yet a very low number of opportunities and a low login frequency. Based on this behavior, we labeled them the “Win Loggers” persona. This persona is driven by winning, and is characterized by the user only logging won opportunities and omitting in-progress or lost opportunities. The reason for this behavior may be that the user wants to avoid negative feedback, or being perceived as “losing” by management or peers.
• Adoption plan: Once we identified which personas use Salesforce, we created targeted adoption plans for each of them. For example, our Win Loggers weren't using Sales Cloud effectively. The fact they were not logging all of their opportunities or collaborating with each other caused issues with reporting and overall pipeline management. To address this, we created a few targeted campaigns, one of which revolved around the reporting capabilities of Salesforce and how the user can benefit by using them. We were able to see positive behavior change for this persona within a couple of weeks.

Creating the right user behavior is key to creating a successful Salesforce implementation, and understanding user behavior is the first step in this process. Leveraging cluster analysis will provide you with deeper insights so you can design targeted programs that drive engagement and realize the tremendous value of Salesforce.