How many times as a customer, did it happen to meet a seller who did not understand your needs?
At the same time, how many times as a Sales Rep, were you unable to catch a client’s interest?
Whatever the case is, there is always an optimal situation that would allow us to have an higher chances to close the deal. Most times, this situation is attributable to a simple and natural factor: the affinity between people.
Whether you are in a B2B or B2C business, it is still a business made between people, and the affinity between 2 or more subjects is as natural as it is rare.
Mapadore has developed a digital assistant which, due to its natural aptitude, is called Profile Matching.
The secret of this tool lies in its simplicity: assign the best seller to a specific customer.
You are probably wondering, how does it work?
Mapadore performs out skill/social matching between customers and salespeople to maximize closing opportunities, putting the most suitable salesman or technician in front of customers’ needs.
In short, the Profile Matching process takes place in three phases:
- When installing Mapadore, you choose which are the priorities of the individual commercial: its strengths, skills and the type of ideal customer.
- Once the lead is acquired, Mapadore profiles the customer based on the categories inside of the CRM
- Finally, Mapadore identifies the ideal match between the customer’s needs/typology and the ideal Sales Rep and independently assigns the leads according to the characteristics imposed by Profile Matching.
But it doesn’t end up here.
Machine Learning allows to update the Digital Agent new parameters, based on previous successful sales stories. Thanks to this learning process, Profile Matching keeps track of the sales stories and performs always more effectively.
Operating Case Study: AbitareIn
AbitareIn is a Real Estate Agency operating in the Milan area. It has increased its number of customers by 40%, simply speeding up the appointment process of the real estate agent on the website and, above all, sending the most suitable person to meet the customer.
But, how did AbitareIn know who the customer was before meeting him?
In other words, how is it possible to predict customers’ attributes?
A web form can be useful to collect information and broadly outline the type of customer. In this case, the age of the interested party and the size of the apartment were enough to define a profile type.
The algorithm is able to profile the type of customer based on the answers included in the form and starting from the first interaction. Also, the algorithm considers running opportunities and increases the probability of closure.
Moreover, thanks to another Mapadore’s tool, the Omnichannel Integration, instead of allowing the web user to request a meeting with an agent and then set a timetable, Mapadore allows you to immediately book a time slot, immediately after completing the form.
Mapadore, in fact, performs a simultaneous check of who is the ideal commercial and what are his commitments, allowing the web user to book in real time one out of three time slots.
The appointment setting time is reduced drastically and avoids to lose customers during the appointment process.
Just to sum up
In short, Mapadore engine can map the characteristics of your customers and those of your agents
- You can define matching criteria and automatically assign leads and opportunities to Sales Reps
- Collect more information about the customers connecting social media profiles
- Consequences: increase in turnover, greater loyalty, improve customer experience, better distribution of work, more knowledge of the customer