Transforming revenue enablement with contextual search, AI and more

Chandramani Tiwary
June 8, 2023
Table of Contents

Search-and-discovery of sales content is one of the primary functions of sales enablement tools. The basic value prop is to organize content in a central repository so sellers can find the latest content independently. Unfortunately, this fundamental problem is still unsolved in many current sales enablement tools.

In this blog post, we’ll try to understand why search is broken and how GTM Buddy aims to fix search to boost rep productivity and effectiveness.

What’s broken in search today?

Browse any random selection of reviews of enablement solutions on websites such as G2 or TrustRadius, and you will find users complaining about search inefficiency and the time it takes to find the right content. It may be the most common grievance sales teams have against legacy enablement platforms. 

But why is search broken to this extent? Here’s a list of possible reasons:

1. Content management nightmare

Over Reliance on file/folder names

Current Sales enablement tools rely heavily on file names to surface results. Therefore, for accurate search results, sellers need to know the file names they are looking for. 

Research firms like Forrester have underlined the importance of file names. While focusing on just file names to help with content findability may be a good starting point, the process is painful and insufficient. 

Imagine a case study for a customer (ACME) in healthcare that gives glowing reviews for the Zendesk Chat feature. There are many potential file names based on different search contexts. For example, “Case study: Zendesk Chat, ” “Case Study: ACME,” or “Case Study: Healthcare.”

You start seeing issues with relying only on file naming conventions for aiding discovery. There are too many good file names and only one possible file name that can be used.  The same problems arise when using folder names to aid discovery.

Over Reliance on manual tagging

Almost all sales enablement tools today require content to be manually tagged. Manual tags can help tweak the relevance of a document while listing the search result. But, this process is not without problems:

  • Someone must manually tag and ensure all new tag taxonomy entries are back propagated. If not, such content is considered relevant by the search engine.
  • Manual tags don’t help distinguish which documents are more relevant; all tagged documents are considered equally important.

2. Problems with full-text search

If no file names or manual tags match, tools today revert to full-text search, which results in too many irrelevant search results. For example, consider a seller searching for the term “Box case study.” They might be pursuing DropBox, and if there is no file with such a name, then all case studies which mention `out of the box` capabilities become part of the search result.

Many reviews of sales content management systems in G2 and TrustRadius underline this point. 

3. Not built for sales teams

Sales enablement tools employ generic search algorithms. These were not built with an inherent understanding of sales as a domain. Search engines for sellers should understand that price, pricing, budget, cost, and other similar keywords mean the same thing as migration, implementation, cost to move, and so on.

4. Non-contextual search

Most sellers don’t search for content as a hobby 😀 They do it in the context of an opportunity. For example, a seller searching for pricing is either looking for pricing against a competitor, for a region or a particular customer segment or for a product feature. Unfortunately, sales enablement tools today don’t have the capability to account for the search context.  

How GTM Buddy solves search

GTM Buddy's just-in-time enablement platform was built to provide sales reps with the knowledge and resources they need, right when they need them. To achieve this, the platform takes a more evolved approach to search.

1. Semantic layers

GTM Buddy’s search is semantic and contextual. Our contextual intelligence platform has the following capabilities to understand the semantics or meaning of the search query:

General language skills

GTM Buddy’s intelligence layer has state-of-the-art general language skills. GTM Buddy understands the commonly used synonyms used in search terms. For example, it understands that

  • Presentation, ppt and PowerPoint – mean pitch deck
  • Customer success stories, customer examples – mean customer evidence

Our AI layer understands the distinction between American, British, Indian, and other English language variances too. For example, between “color” and “colour.”

Similarly, it also understands singular and plural variations of words.

Domain-specific language model

Our language model is trained specifically for the sales domain. Our search engine understands common sales concepts and can expand the meaning of search terms to include these concepts. For example, a search for “Value” or “Cost of Ownership” will include documents that talk about ROI or return on investment.

Domain ontology layer

GTM Buddy has the capability to understand your business. Our intelligence platform develops a fundamental understanding of the products you sell, the internal and external synonyms those products can be referred to by, the product's capabilities, and so on. The same applies to other fundamental constructs like competitors, customers, regions, etc. 

We achieve this using a product construct called Business Vocabulary. Business Vocabulary provides a quick and effortless way for GTM Buddy’s intelligence platform to gain clear context around your business.

Imagine you are selling a product called  SupportGenie. Internally it is referred to as Knowledge Base, and prospects looking for such a solution might use the terms like Q&A system, support automation, support bot, etc. 

Our Business Vocabulary allows us to understand all three dimensions. You can create a vocabulary value called SupportGenie and add Knowledge Base, Q&A system, support automation, support bot, and question and answering as related keywords. A search of any of these terms will surface documents indexed with SupportGenie.

2. Doesn’t just rely on file names

GTM Buddy’s Intelligence Layer parses through each piece of content, and just like Google, it auto-indexes content based on the defined business vocabulary. GTM Buddy builds context on content that aids search and discovery and doesn’t need to rely on just file names. 

Let’s look at the previous example once more. The Zendesk Chat case study will be analyzed and auto-indexed with the correct industry (Healthcare), region, and product (Zendesk Chat) and, therefore, will be discoverable against all possible queries. 

Search by intent (content type) and entity (business vocabulary attributes)

Instead of remembering file names, sellers can search for what they are looking for, and GTM Buddy’s NLU-based search engine will surface the most relevant document(s). 

For example, they can search for “Customer Success stories for Healthcare,” and GTM will surface case studies, testimonials, and customer reviews from customers belonging to Healthcare Industry.

Search by job titles and persona

Sellers can quickly find messaging, questions to ask, and FAQs relevant to the persona by searching by job titles or persona names.

Optimize full-text search

Any search engine needs to parse all the text in a piece of content. The problem arises when the entire text is used to rank search results without any context.

GTM Buddy’s approach is different:

  • When auto-indexing is run on a document or set of documents, it processes all the content, extracts keywords(tags), shortlists the keywords based on their relevance to your business (business vocabulary), and stores them.
  • These tags are then used to make the search and recommendation faster.
  • It produces a condensed (most important) representation of the document or its content. The tags created through auto-indexing try to represent the whole document by extracting the topics most discussed in the document.
  • Instead of searching through individual pages of every document in run time while searching for a term, we use this condensed representation. 

3. Built for sellers

GTM Buddy has been built from the ground up, keeping sellers in mind. Our search engine is built specifically for sales.

Understands B2B sales and your business 

The search engine understands sales concepts and similarities between search terms. With business vocabulary, sellers can search for the language they understand instead of memorizing how the content is created and stored.

Is contextual

Sellers search for content based on what they are currently working on. GTM Buddy provides sellers with the ability to search against an opportunity, account, or lead. All updated CRM fields are considered while presenting the results.

For example, a seller can search for just “case studies” against a deal ACME, selling the product Zendesk Chat to a customer in Region APAC. GTM Buddy will show the most relevant case study, which is auto-indexed with the product “Zendesk Chat” by a customer from  “APAC”. 

  1. Search in GTM Buddy’s Chrome extension considers the opportunity/account/lead context to rank relevant content
  2. Dedicate the inApp landing page for searching against an opportunity/account/lead
  3. Contextual Search includes all content relevant to a deal, such as similar customers and related customer evidence, competition and persona messaging, Infosec, and relevant product overviews

Pushing the envelope: Generative AI and search

Generative AI has the potential to transform search by revolutionizing how users interact with search engines and improving the accuracy and relevance of search results. 

GTM Buddy is also leveraging this technology to make our platform even more helpful for sellers - with Ask Buddy.

Ask Buddy's generative AI-powered guided selling solution delivers real-time guidance that elevates rep performance and accelerates revenue growth. It replaces static playbooks with just-in-time enablement based on the opportunity context, buyer engagement, and relevant sales content. So, instead of surfacing files against a search term, Ask Buddy generates summarized answers to the search query from across multiple files. 

Reps can now quickly respond to prospect emails, address buyer objections, and prepare for crucial conversations in real-time with Ask Buddy.

In conclusion

The ability to find the right content in time with minimal effort is a crucial use case revenue teams seek in an enablement platform. Based on the capabilities discussed , GTM Buddy’s search is fundamentally better and helps sellers do their day-to-day tasks more efficiently and impactfully. 

About the author


Chandramani Tiwary

Chandramani Tiwary is a co-founder of GTM Buddy, where he leads the AI efforts for building a just-in-time sales enablement platform. Before joining GTM Buddy, he was head of Data Science at Zomato and a founding member of the Data Science Team at Gainsight.

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