Sales Enablement can make a significant impact on how enterprise organizations improve the productivity and success rates of their people, and thousands of the world’s leading businesses are already experiencing those benefits in how they empower their customer facing teams every day.
The Problem of Relevancy
However, no matter how smart you think your sales enablement approach is, many sales reps do not make use of available content, leaving sales performance wanting. Search does little to help, usually returning irrelevant information - The problem is relevancy – Training and collateral is more effective when provided in the context of existing opportunities.
We need a new way to ensure that content is available to help sales representatives drive deals more effectively, and training and eLearning that help sales reps know HOW and WHERE to get the skills they need.
Ontologies to the Rescue
What is an ontology? According to the Oxford Dictionary, an ontology is “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them.” An ontology is an approach to data science that allows for the connections between information sets that is not possible with traditional search based approaches.
But of course for an ontology to be successful, every different field of businesses will need its own ontology to organize information that makes sense to them into data and knowledge. This reduces the complexity associated with managing and finding data.
For sales enablement, an ontology can have a major impact on how data is linked. To simplify things, lets define an ontology to be the abbreviated language used by sales reps to describe their opportunity and leads; “Company {A} is in Industry {B} and they are looking to buy Product(s) {C} for the buying criteria (features & benefits) of {D}. Our competition is {E}.”
The ontology can be a abbreviated dictionary: Subsets {A} {B} {C} {D} {F} as a set represent the sales reps and sales management knowledge about the opportunity – the sales scenario. If you think about it this is how salespeople relay information to their managers and how they record it in CRM. A full ontology dictionary covers all the possible opportunities – all sales scenarios.
So, an ontology can be used to do things that have not been possible before - in a way that helps sellers and managers to be more successful:
- Match the needs of opportunities to available content
- Compare deals for similarity
- Find the deals that are missing content or sales experience
Why Use an Ontology?
When it comes to helping a seller to be more productive, an ontology accounts for all permutations – it can be used to demote false positives. For Example, think of an opportunity where a sales rep is selling product A into industry C. A case study showing a similar customer buying the product would be promoted, while a catalog (that describes many products and markets) would be demoted and kept away from the sales rep.
An ontology can also help make content recommendations more contextual for a seller. For example, product and Industry may define a use case and/or case study, whereas a competitor and product may define a competitive sheet.
How Can I Create an Ontology for My Business?
Creating your own baseline ontology for your business is simple. The base ontology can reflect what sales records are in the CRM, and be based on what is contained in the CRM fields. A field picker can help choose which terms to pick.
On top of the base ontology, you need to define a thesaurus between marketing and sales. The thesaurus should combine an ontological analysis of the sales pipeline, an analysis of collateral, and then a program to identify the gaps and build the thesaurus.
Finding the Gaps
One key deliverable of a data science based ontology is the ability to identify the gaps in the content that marketing has created against the work that the sales teams are doing. Imagine a world where the AI doesn’t just identify content that a seller should use to increase the likelihood of success, but also provides guidance into missing content that would help the seller to close a deal if it existed.
The diagram below shows a situation where a seller has an opportunity to sell a product (DH2) to a government customer against a competitor (Comp 1). The AI software uses the ontology to identify that there is no case study or competitive analysis that specifically helps the seller in this deal.
