Tag taxonomies are at the heart of every content management system or CMS. Sales enablement platforms and digital asset management (DAM) solutions are no exception.
And yet, creating, adding, and managing asset tags in your CMS will likely top the tasks most disliked by sales enablement practitioners and product marketers.
Does the effort enablers put into organizing content using tag taxonomies lead to content being discovered and used by reps with intended ease?
Probably not! (if G2 reviews are any indication)
We feel the time is ripe for a shakedown of the status quo of tag taxonomies.
So, let’s examine the current lay of the land when it comes to tags and tag taxonomies in sales enablement and how technology can help alleviate the burden of work involved while multiplying the benefits.
What is a Tag Taxonomy?
Most of us are familiar with the concept of tags. Simply put, tags are the keywords or phrases we assign to content to help find it later. A tag taxonomy defines the relationships between tags, such as how they are grouped together. Think of them as a system for organizing tags.
Here’s a basic structure of a tag taxonomy:
How Tag Taxonomies are Used in Sales Enablement Platforms
In a world of ever-expanding information, efficient organization and easy discoverability of content are critical to their usefulness. This is true for sales enablement and marketing content, too.
Sales enablement platforms use tag taxonomies to help sales reps find and use the content they need. For example, a sales rep might be looking for a specific case study, or they might be looking for some other sales asset that is relevant to a particular industry or geography. The tag taxonomy helps the sales rep find the right content asset (or assets) without having to search inside folders and files manually.
Every sales enablement platform has a tag taxonomy.
While differently named, these tag taxonomies have a similar operating procedure - with minor variations. In theory, tag taxonomies are designed to help:
- Facilitate search and discovery of content: A well-designed tag taxonomy can make it easy for sales reps to find the content they need. Some vendors use tags in their search; others use them only for filters. So, the mileage you get out of them can vary.
- Organize content: Tag taxonomies can help you organize your content in a way that makes sense for your business. However, content organization can be challenging considering the quantum of assets, the number of stakeholders involved, and recurring people changes.
- Deliver rule-based recommendations: The most talked about use case of tag taxonomy is using it to enable reps with predictive content recommendations. Enablers can create rules that recommend content to sales reps based on the context of an opportunity.
- Create personalized experiences for sales reps: Tag taxonomies can be used to create personalized experiences for sales reps by showing them content relevant to their interests and the buying stage of the deal.
- Track the performance of content: Tag taxonomies can be used to track the performance of content by tracking the number of times each tag is used and the number of times each piece of content is viewed.
The Trouble with Tag Taxonomies
With many of these vendors, tag taxonomies are managed manually. Enablement, Product Marketing, or any other team managing the content is expected to:
- Create the tag taxonomy: Build the nested tag hierarchies and tags
- Tag each piece of content manually: Upload content and add tags to each piece of content
- Changes in tags: Whenever your tag taxonomy changes, remember to manually go into the assets & re-tag the assets
While it may look simple, it is not. Beyond the upfront effort of tagging the assets uploaded to the CMS, maintaining these tags is a more challenging responsibility.
And therein lies the risk.
Tag taxonomies are fragile because any changes to the tags can break the carefully built house of cards. For example, if you delete a tag, you might also break the existing rules based on that tag. The whole exercise fails its key purpose - surfacing relevant content when needed by reps.
This can be a major problem, especially if you have a large and complex tag taxonomy. In some cases, rebuilding the entire tag taxonomy from scratch can even be necessary.
Here are some other challenges to consider:
1. Needs planning and resources
It takes significant thought and planning to create an effective tag taxonomy. You need to consider the different types of content you have, how people will search for content, and the relationships between different tags.
You will need to ensure an agreed-upon tag taxonomy across your organization and the team manually tagging content is fully onboard with it. Cross-team alignment is important here. Ignoring this step will likely lead to serious implications down the road.
2. Short shelf-life
Even with careful planning, tag taxonomies almost always degenerate faster than you expect and become outdated. As your content changes, for example, you need to update your tag taxonomy to reflect those changes. Or, if the RevOps team changes the picklist fields in the CRM or restructures the verticals (not in your control), you may have to redo the tax taxonomy.
Tag taxonomies can be challenging to maintain. It takes time and effort to keep track of all the tags and their relationships.
Lack of discipline can be disastrous here. Everyone on the team may start creating their tags - for example, ‘Case Studies,’ ‘Case Study,’ ‘Customer Success Story,’ ‘Customer Evidence,’ ‘Customer Testimonial’ - all for the same asset.
Additionally, personnel changes without the right foundational context and training can lead to confusion, inefficiency, and, ultimately, the degeneration of the taxonomy.
Implications of Tag Degeneration
When a tag taxonomy changes and the content is not fully retagged to reflect the changes, problems arise. You may start experiencing the following challenges:
1. Reps can’t find content
The primary purpose of a content management system is its ability to organize content in a way that makes it quick and easy to find and use. But, a broken or messy tag taxonomy leads to the all too common complaint, ‘I can’t seem to find the content in our repository.’
2. Content recommendations are broken
Either reps see irrelevant content recommendations or don’t see any recommendations at all. In both cases, rep productivity is negatively affected. Furthermore, the more complex your tag taxonomy, the longer it will take to fix the system.
Solutions in the world of AI
Gartner has issued directional guidance that all sales enablement platforms should move from manual tagging to AI-driven automated tagging of content. The industry is struggling to catch up!
Unlike traditional sales enablement platforms, GTM Buddy was built on an AI foundation. The platform leverages AI to solve for the limitations of manually-administered tag taxonomies, including their degeneration. Here’s how:
Let’s start with a key term that you would want to know - Ontology.
The Oxford Dictionary defines Ontology as “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them.”
Consider a simple example.
Let’s say your business competes with Salesforce in certain areas. Salesforce uses terms like Einstein, Force.com, AppExchange, etc., to describe its extensible platform ecosystem.
GTM Buddy’s AI models can leverage this information to understand the nature of content in your content repository. This offers several benefits.
1. Automate content tagging
Since the AI model understands your business ontology, there’s no need to tag the assets manually. If there’s a piece of competitive content that references Einstein, our AI model can automatically:
- Relate this to Salesforce
- Identify the content as competitive content
- Automatically tag the content appropriately
Not only that, the AI model also connects this to the opportunity context, allowing GTM Buddy to provide contextually relevant information to sellers in their flow of work.
2. Tag new content
Whenever new content is added to GTM Buddy, the AI model tags the content automatically. You always have the freedom to review and change tags if necessary. If you make changes, the AI model learns from the changes that you have made.
3. Reduce the number of tags
With an extended understanding of the language of your business, you don’t need to tag your content extensively. The AI model understands the related terminology automatically and delivers search results accordingly.
4. Update tags & manage tag taxonomy
Update your business vocabulary centrally, and re-run the tagging engine to update the tags of your content appropriately. These can include the addition of new phrases (aka tags), updation of the existing terminology, and so on.
5. Support language variations
The platform supports variations of a search query based on the language used by the user. For example, customer evidence can be referenced as "success stories" or "implementation examples" by sales reps in a sales organization. The AI model understands this and surfaces customer evidence assets for both keywords.
6. YOU remain in control
While the AI model automates the drudge work, you remain in control of the language of your business. You can override the tags that the model creates for you at any time. As you make changes, the AI model learns from these changes and evolves continuously.
Do you want to take this for a spin and try it out for yourself?
Talk to us!