When measuring adoption it’s useful to see the number of logged in users for a given period as a percentage of the total user base. Since Salesforce reports can only report on what data is visible (as is to be expected) it’s not possible to compare logged in users to total users. There is a way around this by using a joined report.
- Create a joined report using User as the primary object. This will create a Users block.
- Drag a field from the Users object over to an empty space in the preview area. This will create a second Users block. It’s a good idea to use a field which is required for reporting purposes since the report will be grouped at this level.
- Filter the second block on logged-in users for the desired time frame.
- Create a cross-block formula field using the Record Count summary fields from each block to divide the number of logged in users from block 2 by the total number of users from block 1. This field will typically be called Logged In Percentage or something similar. Change the formula to field type to percentage.
One of the more painful administrative tasks faced by Sales reps and account managers is keeping contact lists up to date. Sure, many platforms offer mail and calendar integration but there is still some work to be done, i.e. the contact has to be loaded in the contact application, such as Outlook, before it can be added as a Contact in the CRM platform.
Recently, Apple introduced a feature whereby, an incoming caller number is tagged with a potential contact name based on iOS matching the incoming number with a number in the email signature of an exchange with the contact.
Salesforce Einstein provides a similar benefit which is called Automated Contacts.
This is a simple but beneficial time-saving device which highlights the benefits of embedded AI technologies in a CRM platform
CRM vendors are increasing their investments in AI technology and making it available in their CRM platforms to support decision making and to trigger actions.
AI encompasses machine learning and deep learning as well data science methods. It is closely linked to the field of data analytics.
AI is about thinking machines. Data is ingested and patterns are detected using statistical models. These patterns can be used to predict behaviour and a host of other outcomes.
These benefits include predictive scoring (lead scoring), forecasting (predict future revenue), recommendations (for cross sell purposes) and early warning systems (for retention). In other words, AI will eclipse what generic algorithms offer, will enhance salespersons’ intuition and will intelligently monitor customer activities.
Other benefits include chatbots, virtual customer assistants, intelligent social media monitoring and automatically logging customer interactions.
Having made the investments the software marketing machines are kicking into high gear so there is an element of hype. However, the benefits for successful early adopters could be significant so be on the look-out for opportunities to experiment with the ever-expanding and quickly maturing AI toolset.
Finally, as always, as with all things CRM the quality of the data will make the difference between a mediocre outcome and a great outcome.
CRM (Artificial Intelligence) AI vendors and tools include:
- Conversica – automated sales assistants
- Introhive – data automation and sales acceleration
- Salesforce.com Einstein – AI built into Cloud products
- DigitalGenius – automate customer service
- Microsoft Cortana – marketing, sales and service analytics solutions