Time is money for sales reps and other go-to-market teams, meaning being able to do more in less time and focus on critical tasks has become more important than ever.
Salesforce reports that reps spend only 28% of their week actually selling. To boost productivity for our customers, we built major innovations in the Mindtickle platform: Copilot AI-powered search and an enterprise search connector interface.
These technologies reshape how employees access and use information, accelerating productivity along the way.
Here’s how.
Copilot powers Mindtickle search
Building on our recent announcement of introducing generative AI to the platform, search is now becoming more powerful with the same technology.
Within Mindtickle’s platform, training programs, modules, marketing collateral, assets, calls, reports, and analytics all produce vast amounts of data. Sometimes, finding exactly what you are looking for with a keyword-based search algorithm amidst thousands of training, collateral, and calls can be limiting.
This is where Copilot’s AI-powered search comes in.
It is not just a keyword search, instead, Copilot understands the meaning and context behind each search query. As a result, Copilot provides precise and relevant results.
Copilot search provides:
Copilot goes beyond keyword matching, ensuring you get exactly what you need.
You can explore ideas and concepts, opening new avenues for exploration and discovery.
As your data grows, basic keyword searches become less effective, especially for enterprise organizations. Copilot can make sense of vast amounts of data in seconds.
Enhancing your search with generative AI
By leveraging cutting-edge Machine Learning (ML) and generative AI technology, Mindtickle generates semantic embeddings for your documents, enabling our search to understand context, not just keywords.
This means your users can find what they need fast, which can mean the difference between a deal won or a deal lost.
Expanding the breadth and depth of search
Copilot uses semantic search to deliver the most accurate results to users. These additional searchable elements include:
Searchable entities in Mindtickle include all training content, assets, recorded calls, files, and more. Our ML model scans and indexes all content in the platform for all entities.
Each item is searchable on a specific set of searchable attributes. For instance, an asset could be explored by name, description, attributes or tags, and any content or text in that file. Additionally, contextual filters are tailored to the entity type.
For even more accurate search results, Mindtickle uses query vectorization, where the ML model can predict similarities between searchable entities and terms like words and images. This supports precise searching of all elements of documents and content in Mindtickle, providing more accurate results by understanding the query’s meaning and the documents’ relevance together, bringing context-rich output to life.
How semantic search is different from keyword search
Let’s look at an example of how this impacts a seller’s everyday work.
Adam, a sales rep is preparing for an important meeting with a prospect. The prospect is at an investment company, particularly about their data security and Adam needs to check if the product he is selling meets their security requirements.
Traditional keyword searches
AI-powered semantic search
Most importantly, the overall search experience now provides better discoverability and accessibility with the experience of search being unified. This helps learners search for any type of materials they are looking for in a few clicks.
Mindtickle’s Copilot AI-powered search and integrated enterprise search are your keys to unlocking peak productivity. Get ready to work smarter, not harder, with our transformative technologies, and discover a world of limitless possibilities in your data.
By Poornima Mohandas
By Vivian Batman