Tableau CRM is the new name for Einstein Analytics reflecting the Salesforce acquisition of Tableau. There are a number of resources to learn Tableau CRM.
Data science application called Northstar which introduces a virtual data scientist (VSD) component. This makes it easier for non-data scientists to visualise and link data which trains ML algorithms.
“Even a coffee shop owner who doesn’t know data science should be able to predict their sales over the next few weeks to figure out how much coffee to buy,”
Consider these metrics.
- Leads by source
- Open activities
- Open cases / issues
- Open / pipeline opportunities
- Opportunities past due
- Closed opportunities
- Sales cycle
- Pipeline by stage
- Sales by closed date
- New business vs upsell ratio
- Win/loss rate
- Product gaps – forecast vs actual revenue
If an Org has two nodes immediately below the prime node there is an issue with including all records owned by users in these two nodes.
Under the prime node CDV there is a CEO and a Co CEO node.
When defining the scope of records in a report filter the prime node, CDZ, cannot be selected.
A choice has to be made between one or the other CEO node.
This is not a problem in a list view since all opportunities can be selected in the record scope without having to choose a node other than the prime node as is the case for reports.
The workaround is to either use a list view or create the report in Classic where all opportunities can be selected. Note that if you edit the report in Lightning after it has been created in Classic it will assume the above behaviour and the report will be limited to the first CEO node.
Update (4th Nov 2018): This is a known issue and will be fixed in a Winter ’19 patch
Some updates which caught my eye
- Develop apps from spreadsheets using new low-code options – Check it out here.
- Log meeting notes using Einstein voice. Notes will be automatically related to the correct Client. Einstein voice also allows for voice bots Another link to the Salesforce blog.
- Salesforce partners with Apple. Details here.
1. Pick 3 burning issues to fix / improve or new initiatives to generate value. What is important is having a clear picture of the full vision and selecting a technology stack which will support adding functionality as required.
2. Identify metrics to measure the benefits for e.g. increase conversion of website visitors by x percent, decrease admin time to process sales by x days, etc. Start with a baseline measure even if it is an estimate. Build dashboards and reports which can readily show the improvement in the metrics.
3. Identify one person or team to drive and deliver the implementation. Has the mandate to make decisions or can easily get to decision makers.
When it comes to managing the overall change:
4. Ensure that the leadership team is fully bought-in and understands the impact of the new system on the ways of working (the change will not only be a system change but will require changes to processes and how people work)
5. Make the case for change and ensure that it is commonly understood (the why, what, how, etc) across the organization. Most people would agree that emails and spreadsheets are not the most efficient way to work but changing well-established habits and getting someone to log onto a new system and do a task differently requires change effort. Must have a clear answer to the question ‘What’s in it for me?’
6. Don’t underestimate the need for training and communication. These are just as important as the technology and directly lead to better adoption of the system.
Zoho Creator is a useful and versatile platform. One of the more common requirements, especially when creating a new app, is to import data. While it has a decent import tool there is a limitation worth noting.
Using Numbers on a Mac I was unable to select a Numbers date format which was compatible with the Zoho form date format. The format is dd-MMM-yyyy. This cannot be changed – or I couldn’t easily find where to change this. Numbers does not support this format. As a result I had to use Google sheets.
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