Scalability at Mindtickle
Mindtickle right now is at a phase where the systems need to be scaled. We are currently investing in building a platform that is scalable, can do data analysis, and can integrate with third-party systems and that’s where all the knowledge comes together. In my personal journey, there are three things that are common – one is enterprise solutions, second is data analytics and third is building large-scale systems. When a company needs to scale to its next level, all these three things need to come together and that is what we are doing at Mindtickle.
Sales Enablement Verticals
Every enterprise company has a sales division; if we look at the sales enablement platform, it covers four different verticals—the first is learning solutions, where salespeople are constantly learning about what to sell, what to pitch, and how to pitch. They need to continuously learn and complete certifications.
The second is the management and creation of content. There are various ways in which content is created—whether it is PDFs, PPTs, or videos; how you make this content engaging and useful for the learner while meeting the goals the company has set is extremely important.
The third is conversational AI. Over the last three years, a significant portion of sales communication has been taking place online and while these calls are recorded, the AI can note the key moments of the call and provide feedback to the salesperson.
The fourth vertical is revenue operations. It is where all the sales deals are stored, to learn how the deals are coming in and progressing and what the probability of the deal converting is.
These four pillars constitute the sales enablement platform and behind these pillars is a platform that is doing user management, storage, data analytics, integration, and workflows across these 4 pillars and that’s how the entire sales enablement industry comes together.
Integration of Platform
There are multiple types of integration that happens across the platform- there is integration with the user – we call it directory sync. The second would be integration with content, called content sync (this content could be in Sharepoint, Dropbox, AEM or it could be in multiple places at the same time). The third integration is – Call AI which needs integration with Zoom, teams, calendar, etc.
When we look at enterprises, they will always have their own set of systems they are working with, to be a productive system we need to work with their environment and set of tools. That’s what every enterprise company also focuses on and that is what Mindtickle does with its solutions. It can get very difficult if the platform approach isn’t put in at the right point or the generalisations and abstractions are not applied at the right time.
Data analytics is a key functionality to the sales pillar as there is data getting generated from the learner’s activity feed, conversational AI calls, and the sales pitches being made. When you bring all of this data together, you can easily answer how effective a sales engineer is and what kind of extra coaching they would need and what’s working for them. This can help build an effective organisation. For instance, an engineer would have some core skills like coding, debugging, and performance – similarly there are some core skills that would make a salesperson effective. How would you map the efficiency of a salesperson on a graph – you need data from different internal sources and external systems in order to map the effectiveness of the sales organization. So, that is where data analytics and right modelling come into the picture. This predicts whether revenue holds for an organization will be met or not and how will it all come together. Skill analysis is a continuous journey for a salesperson to learn and deliver the content and earn certifications. It is not a one-time onboarding thing, it is a continuous process. Companies hire great talent but they have to continuously train and coach the sales teams due to the nature of the job and its continuous change in trends.
Authored by Richa
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