Glossary
Content Analytics
Insights on content usage and buyer viewing, which assets move deals, which stall them, and where teams need clearer, simpler, more relevant content.
Content analytics is the admin level view of how sales content performs across your whole organisation. It combines what sellers actually use with what customers actually engage with after sharing, so you can improve the content system over time instead of guessing.
Also known as: sales content analytics, enablement analytics, content performance
Why content analytics exists at all
Most teams have the same problem, they create content, publish it, and then hope for the best.
But “published” is not the same as “used”, and “used” is not the same as “effective”.
Content analytics is the feedback loop that closes that gap. Not at the level of one deal, but across many sellers, many customers, and many shares.
In Salesframe terms, it sits on top of a simple workflow. Teams keep materials in one library, sellers build customer specific decks, share them as links, and you can see basic engagement on what was opened and viewed. Admins can then look at aggregated patterns across seller usage and customer engagement.
That aggregated view is the point. It helps you create less content that nobody uses, and more content that actually survives contact with real selling.
Two sides of content analytics
Seller side analytics answers a blunt question, what do your sellers present, reuse, and ignore when they are busy and trying to get through the day. You see what content shows up in real meetings, what gets reused across accounts, what never leaves the library, and where people keep improvising because the official version is too heavy, too generic, or simply not useful.
Customer side analytics answers an equally important question, what do customers open, view, spend time on, and ignore after you share. When sellers send a shared presentation link or a trackable link, you can see which parts were opened and viewed. That gives you a view into buyer attention, especially when your content gets forwarded internally and has to stand on its own.
Looking at only one side creates blind spots. Seller adoption alone can make you celebrate a deck that customers barely touch. Customer viewing alone can make you optimise content that sellers avoid because it is hard to find, hard to assemble, or awkward to present. You need both to understand the full path from “available” to “used” to “engaged with”.
Seller-side signals you can learn from
A small set of slides gets reused everywhere, it is a clue that your core story is clear, and the rest might be clutter.
Sellers constantly reorder or rewrite the same sections, it usually means the message is needed but the format is fighting reality.
New hires build decks with high variation, it points to onboarding gaps or unclear standards, not a motivation problem.
Certain packs get opened but rarely presented, that often means “good idea, wrong shape”, like too long, too dense, or too abstract.
Sellers keep creating their own “local versions”, it is a signal that your global master is missing market specific proof points or examples.
Content that never gets used still creates noise, it makes the library feel bigger than it is and slows everyone down.
Customer-side signals you can learn from
Customers consistently spend time on one section, it tells you what they need to make a decision internally.
Customers open the link, then jump straight to practical parts, it is a hint to move those sections earlier or cut the warm up.
The same link gets opened by multiple people, your content likely travelled internally and needs to make sense without a live narrator.
Certain pages get revisited more than others, it can signal high interest or high confusion, you need context from the seller.
Attachments or sections are rarely opened at all, they are either irrelevant, buried, or named in a way buyers do not recognise.
Engagement patterns differ by segment, the same pack will not land the same way with a key account and a smaller customer.
How content analytics is different from content engagement
Content engagement is deal level signal, it helps a seller tailor the next step in a specific case after sharing.
Content analytics is the team level view, it helps you decide what to create, fix, retire, or standardise across the organisation based on patterns, not one conversation.
If engagement helps a seller sell better today, analytics helps the organisation sell more consistently next quarter.
The decisions content analytics should help you make
What to retire because it is dead weight and nobody uses it.
What to simplify because sellers keep rebuilding it or customers keep skipping it.
What to localize because the same core story needs different proof points by market, channel, or customer type.
What to make mandatory in customer facing decks because it protects message consistency and reduces random improvisation.
Where onboarding needs support because new sellers are not finding, using, or assembling the right building blocks.
What should be featured in the library or showroom because it reliably gets used and reliably gets engaged with.
Example: improving a launch or seasonal pack
You publish a seasonal cycle pack for a spring push. It includes a short story, a range overview, an execution checklist for stores, display photos, and a simple ordering guide. The pack is clean, approved, and sitting in the library like a proud little folder.
Two weeks later, the admin view tells you what actually happened.
On the seller side, you see uneven usage. Many sellers use the range overview and the display photos, but the execution checklist barely shows up in presented decks. A handful of sellers keep pulling old slides from last year, then adding their own phone photos and a few bullets. It is not rebellion, it is speed. They are trying to make something they can use in a five minute moment inside a store visit.
On the customer side, you look at engagement from shared presentation links. Customers spend time on the visuals and the ordering guide, they skim the story, and they rarely touch the long “how to execute” explanation you placed at the end. In several cases, the link gets opened by more than one person, meaning the content is being passed around internally, and the parts that travel are the parts that are easy to understand quickly.
So you adjust the pack for the next cycle.
You keep the story, but you cut it to the two points sellers actually say out loud. You turn the execution section into a one page checklist that can be used in a meeting and also makes sense on a phone. You move the ordering guide earlier, because it is clearly a key decision input. You keep the display photos, but you add a “best practice” slide with three clear do’s and don’ts, because sellers were improvising that content anyway.
Next cycle, you should see better seller adoption of the key parts because the pack now fits the rhythm of real visits. You should also see more consistent customer engagement because the content is easier to consume without extra explanation.
That is what “improving content” looks like when you base it on behaviour, not opinions.
Common traps
Vanity dashboards, lots of charts, no decisions.
Overinterpreting single events, one odd view does not equal a trend.
Confusing correlation with proof, attention is not automatically revenue impact.
Ignoring segment differences, then blaming the content for not working everywhere.
Creating reports nobody acts on, analytics is not the outcome, change is.
Trust and privacy basics
Use analytics to improve the system, templates, packs, library structure, and onboarding, not to shame individuals.
Look for patterns over time, then talk to the field before you “fix” anything based on a chart alone.
Share insights widely, keep individual callouts rare and purposeful, coaching is fine, public scoreboards are not.