QLFR Artifical Intelligence
|Coordinator||QLFR Artifical Intelligence AB|
|Funding from Vinnova||SEK 300 000|
|Project duration||May 2018 - October 2018|
Purpose and goal
During this spring and summer, we have continued to iterate on the product and have been able to sign 50 new clients, from 5 different countries. The initial results of the project have been very promising and many sales reps have expressed that they have been able to save a lot of time, and been able to create more revenue with the help of our product. We’ve learned more about where to take the product in order to save even more time for the sales reps, and have specific features that we will/have implemented to save even more time for our users.
Expected results and effects
We have been able to show that sales reps are able to save a lot of time by using our platform. Some have said that they have been able to save up tp 20 hours per sales person, while others say around 10. Almost all of our users have increased their revenue significantly using us, and almost all have expressed that they have a positive ROI by using our tool. We had as a goal to have between 500-1000 sales teams using us a year from April 2018 and we now have 50. Even though that number is high, we think we could have reached a higher number by having a larger sales team.
Planned approach and implementation
We have learnt more about what a company considers a good prospect and how these are evaluated. Information retrieval of prospect data, together with grouping and sorting of this data has been key to the success of this project. This is also where we feel we´ve made the most progress. All sources we consider reasonable are now covered in an efficient manner. The matching algorithm has become considerably more efficient and returns a very small amount of false positives. The next step is locating false negatives.