Leveraging Einstein AI in Service Oriented Business
Service-oriented organizations and divisions face a variety of unique challenges including ever-evolving expectations of nearly immediate resolution and availability and also fast and intelligent engagements across the whole customer service ecosystem. The harmony of aligned and intelligent engagements across call-centers, online communities, e-communications and digital engagements driving customer satisfaction is truly becoming table stakes in our hyper-connected world.
To stay ahead of the curve, more than 50% of companies are or will be exploring how artificial intelligence (AI) solutions can support their internal teams in support and service to their customers1. In this installment of our Einstein Series, we will focus on three key dimensions of service in today’s environment:
- The challenges that service organizations face internally
- How Einstein AI can help close gaps
- The importance of ongoing implementation management to evolve and expand the impact of Salesforce and Einstein AI
As noted in previous articles by my colleagues, there are definitive business, implementation, and licensing considerations that must be examined as part of this process to ensure that Einstein AI is a proper fit within your growing service organization3.
How can Einstein AI Support Your Service Organization?
According to a recent survey2, the specific business challenges that companies are seeking to mitigate are a) call volume reduction with self-service; b) reduction in average customer handling time; and c) increasing the first call resolution rates for members of their call centers.
These certainly are not universal challenges for each company focused on service and with a call center, however they are foundational metrics for a successful service organization. Einstein AI can work across Salesforce to assist on each of these internal challenges – challenges, when turned into positives, that will directly impact the efficiency of a call center and should positively impact the experience of the customer to whom they are in service.
Einstein AI platform tools and services such as Bots can help an organization by both driving customer self-sufficiency, and through customer qualification. Bots can virtually support a customer with order inquiries, standard change orders, returns, etc. This means that your customer call center is taking fewer calls that deal with “information look up.” Further, Bots can help to “qualify” customer information – meaning that when a call is handed off from a Bot to the call center, the customer care agent has information ready and at hand to better manage the call.
These few first examples are specific ways that Bots can reduce call volumes, and increase efficiency of calls that are coming into a service and call center.
Einstein AI, in support of service agents within your organization, can also help to better resolve calls and inquiries when they are first received. Beyond the qualification of the Bots as described above, Einstein AI leverages a solution called “Next Best Action.” This tool allows for guidance of service agents on recommendations for the next step with a customer – in real time. Combined with Einstein’s ability to search previous case articles, find similarities, and surface them to the agent at time of call, Einstein AI provides an operational environment which should drive efficiency and effective customer service needs resolution. Einstein AI can also intelligently research cases and the information in each to help with routing to the correct agent/agent teams depending upon history, capability, and case characteristics.
In working with a client recently with a growing call center, it was brought up that one of the major pain points they have is proper training for an effective service agent – especially when turnover can be higher than in other divisions in their company. Salesforce, Einstein AI, and Magnet360 cannot be a substitute for solid, on-going training of your staff – however, each can be effective at closing the time and skills gap to get service agents up and running effectively season after season.
As my colleagues have pointed out in previous blogs, there are certain standards that need to be achieved before implementing Einstein AI in Salesforce for service centers and call centers. A certain amount of data must exist for Einstein to properly learn and intelligently recommend. The data has to have integrity in the scope of the system data, and you must have the proper licensing for these, and other Einstein AI tools, to be implemented.
Most importantly, in our experience with Einstein AI and implementing Salesforce in service environments, it is the dedication of the organization to supporting the users and measuring the effectiveness of an implementation that will drive short and long term gains from Einstein AI.
Clearly, just from the small glimpses of use cases outlined above, there is a large potential for positive impact from Einstein AI. It can mitigate the common business risks in service centers, it can support the on-going growth of a service team, and it can help drive efficiencies which ultimately drives a growing business.
Service organizations and service leadership who are ready to examine the potential impact of Einstein AI with Salesforce can follow these simple steps as a best practice:
- Understand your business, the challenges and opportunities, which your service organization faces.
- Analyze how Einstein AI with Salesforce can mitigate challenges and amplify your opportunities into positive impacts on your business for your teams and your customers
- Plan out your implementation and on-going training needs so that your teams can be successful
Each organization is unique, and should leverage the power of a Salesforce Partner when investigating the potential impact of Einstein AI and Salesforce.
What are some resources I could access to help further understand Salesforce Einstein?
Some great resources to get you off the ground on Einstein are the Salesforce Einstein Product Page and the Get Smart with Salesforce Einstein trail on Trailhead. The trail is comprehensive from an introduction to Einstein features to practical implementation of some of the functionality. Also mentioned above in this blog post is the Salesforce Einstein Features and Pricing datasheet. The datasheet will provide a summary level overview of many of the topics that we have also touched on in this blog post including features aligned to each cloud, benefits, licensing, and cost implications.
How Can Magnet360 Help?
If your organization is not yet on Lightning experience, review our blog post Top 10 Tips to Get You Started with Salesforce Lightning. We have years of experience with Lightning and have helped many companies in their journey from Classic to Lightning within Salesforce. Don’t let this hold you back, if you’re interested in hearing more about our success in helping clients with this migration, please reach out to us.
To catch up on other blogs in this AI series:
- Salesforce, “Einstein for Service, A-I Powered Customer Service”