Here we'll look at some of the best practices to getting started with Saleswhale, and ensuring a successful experience.
Define clear roles and responsibilities
A typical Saleswhale team consists of:
- Executive sponsors who drive buy-in, direction, and momentum from the top of the organization
- at least one business user to operationalize Saleswhale and manage the Saleswhale app - we usually find business users to also be crucial to implementing workflow changes
- IT / CRM resources to support email set up and integration needs
This pod usually helps build and maintain momentum around Saleswhale, and helps to ensure effective and successful change management when implementing an AI solution.
Phase your implementation
We see the most success when our clients phase implementation across 4 phases, the timespan of each phase usually varies from client to client. We recommend working closely with your Customer Success Manager to plan. Through each phase, we also recommend setting clear goals and expectations, which we will go through in the last section of this guide.
- Phase 1: Does it work?
In this stage, we usually look at metrics indicating that an AI sales assistant works and will be able to help augment your human sales reps in scaling outreach.
- Phase 2: Is there ROI?
We usually start to have talks around CRM integration in this stage. This is also where we begin to monitor meetings booked, pipeline generated, and sales closed to ensure there is ROI.
- Phase 3: Does it scale?
At this stage, we typically see clients start to scale the use of Saleswhale throughout their organization. This usually comes in the form of adopting more use cases across different lead segments or deploying Saleswhale across different geographies.
- Phase 4: Is it sustainable?
This is typically where the product must be finally integrated to ensure sustainability.
Set clear goals and expectations
As you embark on deploying your AI sales assistant, we encourage you to set clear goals and expectations. Based on the different phase of your implementation, we recommend setting slightly different hard and soft KPIs.
Phase 1 KPIs are especially important. We usually recommend setting goals around:
- Interaction metrics - Show that AI sales assistants can reach out to and interact with leads effectively. Email conversation open, response, or handover rates are good metrics to track. We typically recommend benchmarking against your current marketing automation emails, or industry benchmarks in lieu of existing metrics.
- Productivity metrics - Show that AI sales assistants can save time in scaled outreach. We typically measure an average of 3 emails per email sent or received, at a minimum. These may also translate into manpower cost savings.
- Pipeline generated - Show that conversations are being qualified and handed over to sales reps. A recommended bonus is monitoring the number of meetings actually booked and conducted.
- Conversational metrics - Show that persistence works. Here we might look at featured conversations that show your AI sales assistant handling referrals or follow up with leads that are out of office.