Salesforce is the most progressive CRM platform in the world today. There are more than five serious implementations of AI features on the Salesforce platform. These include Service Cloud Einstein, Marketing Cloud Einstein, Sales Cloud Einstein, Commerce Cloud Einstein, and Einstein across all the industry clouds. This is besides other key products such as Slack and Tableau, all of which make Salesforce’s future more certain and positive.
Today we are going to look at three ways in which you can leverage AI features to overcome the challenges that traditional CRMs face today. These include personalization, augmentation and automation.
Across all industries, data is the most valuable resource that all companies claim to have. And we are living through a better explosion age. For example, today companies generate 2 billion gigabytes of data every day. Connected devices, on the other hand, generate 5 billion gigabytes of data every single day.
CRMs help nurture the relationship between companies and their customers by letting them have complete visibility into the customer’s behavior from across all multiple channels and data sources.
Although Salesforce as an advanced CRM can help you manage a large range of scenarios within its standard interface, there is a practical limit as to how much data you can show in a set of the related list while expecting your customer service agents to understand this data and work with it effectively.
Customer expectations when interacting with your company are constantly increasing and taking this into account will help you deliver a great experience. You must endeavor to build better, faster, and cheaper processes for your customer service.
Combining the power of AI and a customer-centric platform like Salesforce is one of the ways of overcoming the challenge of dealing with too much data that is unprocessed.
As already mentioned, we are going to look at three key areas in which we can leverage AI to overcome the challenges of traditional CRMs.
As we already know, the ‘holy grail’ for most users is a data-driven, individually personalized customer journey. To be able to drive loyalty, engagement and ultimately more sales, companies need to combine data intelligently and have it in the context of a consumer, which then allows them to show more relevant content.
And the key to all this is AI, particularly in the form of machine learning models. These models can manipulate large amounts of data and reveal patterns about their behaviors and preferences that we can target with our products.
In Salesforce, the Marketing Cloud is particularly the most advanced in this area. In Marketing Cloud, the tools that leverage AI most include Einstein Engagement Score, Journey Builder, Instant Engagement Frequency, Einstein Send Time Optimization, Einstein Recommendations and Einstein Content election.
In Commerce Cloud, the most advanced AI feature is the product recommendation engine that can be programmed to help recommend products to customers considering what similar customers bought before.
The Einstein Next Best Action is the leading feature in Service Cloud. This feature recommends the next best action that should be taken considering the Salesforce record provided. If you plug in machine learning models, then you get a system that can offer more personalized actions based on callers’ history.
Implementing AI features in your Salesforce Org is one of the best practices to set you on the path to positive, intelligent process automation that guarantees results into future.
When automation is mentioned, the first thing that comes to people’s minds is how to use AI to achieve their business goals. This can often lead to unrealistic expectations about how much automation is possible and practical. However, automation routine processes while at the same time allowing your users to focus on those elements that require genuine human intervention and judgment has business life-changing benefits.
Salesforce offers a host of tools for automation, but very few are pre-built into the system compared to those of personalization. The reason for this is the variability in common processes across industries.
The most classical feature in Salesforce for this area of automation is the Einstein Case Classification and Routing. This feature can automate several routine steps that are important in a customer service case.
Then, there is also Einstein Automate, which is a suite of integration and low-code process definition tools. With Einstein Prediction Builder, Einstein Discovery and by utilizing Tableau CRM, you can use different machine learning models to implement automation solutions for your different cases.
You can also use third-party integration possibilities and if these don’t suffice, you can build your own solutions from scratch on a platform like Amazon Web Services (AWS) and deploy them on Salesforce.
One of the most critical applications that need AI features in your Salesforce Org is the ability to augment sales and staff.
Although automation focuses on efficiency, the kind of efficiency referred to here is a different one. This one does not mean replacing manual processes with automated systems, but rather providing insight and assistance to human workers so that they can focus on their highest-value activities, allowing them to be more proactive.
In order to provide insight and assistance, the most viable solution is to embed intelligent analytics that can provide the best course of action given the customer data. Salesforce has a whole set of pre-built features that can be used in this context. These include Einstein Lead and Opportunity Scoring, all of which function together to qualify and prioritize the right Lead and Opportunities for sales teams to pursue.
There is also Einstein Prediction Builder which you can use to create similar features to the above yourself. Another interesting feature– the instant Account insights, allows you to prioritize information from new sources regarding updates and features that may be affecting your account setup.
Another important tool when considering your customers or internal experts is the Einstein Bots. Bots are used in automating routine transactions and come in handy when determining a customer’s route to help or how to direct experts within your organization to get the best starting point when dealing with customers.
The incorporation of AI features on the Salesforce platform brings with it long-lasting benefits to both your users and your customers. The above use case scenarios should be enough to prompt you to start thinking of how to incorporate AI in your Salesforce org projects.
If you are ready to incorporate AI features in your Salesforce Org project and are not sure where to begin, we can help you design powerful and accurate AI-driven, state-of-the-art solutions that are custom-made to your business needs. Talk to us today or review our Salesforce managed services for details.