People kept asking us: “why are you guys building yet another CRM?”
It’s a valid question as there are many solutions available in this space. The great majority of them however, suffer from very low user adoption, which makes companies using them know very little of what’s really happening with their businesses and significantly limits their growth.
This is the reason why so far at Base we’ve been focusing on making our users much more productive, on building software they will actually love to use. The only way to really ensure user adoption is to make each individual person using your software get a lot of value from it, to make them able to accomplish much more. Hence, our All-in-One Sales Platform combines user-friendly interface, industry-leading mobile apps, and fully-integrated sales productivity tools. This leads to very high adoption rates and allows us to capture up to 30X more data than traditional CRM systems.
Now, being at the forefront of this user-focused revolution in business software, it is time for the next step in our vision. It is time to use our customers’ data to unlock new layers of value for them – on a scale unheard-of in our industry.
We’ve been working on this for a while and now we are very happy to introduce Apollo, the first ever Sales Science Platform:
Apollo captures and analyzes millions of data points from sales activities in real time and delivers quantifiable, actionable insights that have the power to dramatically transform organizations.
Apollo makes it easy for sales leaders to review these insights, dive deeper into contributing data points and key factors, decide which ones to focus on and track their progress over time. Most importantly, they can see a list of recommended actions they can take to have immediate impact on sales performance.
This means that from an engineering perspective we’re building an unprecedented big data product in the sales space, for large scale real-time analytics, that we’ll keep selecting best of breed data technologies (ie. Spark, Kafka, Druid), and finally that we are and will continue to attack problems of extremely high levels of complexity. Yes, we are excited!
Public release date: beginning of 2017