Turn product knowledge into confident conversations and better decisions
In a complex portfolio, selling is a knowledge job before it is a persuasion job. Certainty about what applies is what closes the deal.
From smart calculators to call scripts and data comparisons - ClearMash helps us deliver better service, faster.
With ClearMash, we found true partners for the journey, and together we have achieved Cellcom’s service goals while dramatically enhancing our ability to maximize our knowledge in every customer interaction.
The flexibility in accommodating changes, seamless integrations, and creative solutions made ClearMash a true partner.
Why this matters in sales
A complex catalog is more than anyone can hold in their head. Hand a salesperson every product, each with its conditions, exclusions, eligibility rules and live versions, and a rational behavior emerges: they sell the ones they are sure about.
That instinct protects the customer and the salesperson, and it quietly caps revenue. Options that would have fitted better are never raised. Cross-sell conversations do not happen because nobody wants to promise something that turns out not to apply.
The same uncertainty slows every deal. Comparisons get built by hand in a spreadsheet. Eligibility is checked by asking a product specialist and waiting. Proposals go out with a caveat, and occasionally get corrected afterwards, which is the most expensive way to learn a rule.
New hires feel it hardest. Ramp time in a complex portfolio is measured in quarters, and most of that time goes on learning what is true.
- The challenge:
Portfolio complexity
Variants, conditions, bundles and legacy products that customers still hold and still ask about.
With ClearMash Brain:More of the portfolio in play
Salespeople raise options they previously avoided, because uncertainty no longer carries a personal cost.
- The challenge:
Uneven product knowledge
Salespeople describe the same product differently, and each is partly right.
With ClearMash Brain:The same product, described the same way
The online journey and every salesperson describe a product in the same terms.
- The challenge:
Eligibility guesswork
Whether this customer qualifies is discovered late, sometimes after a commitment.
With ClearMash Brain:Fewer corrections and withdrawals
Fewer proposals have to be revised because a condition surfaced late.
- The challenge:
Slow comparison
Positioning options against each other takes preparation the customer does not wait for.
With ClearMash Brain:Comparisons made in the meeting
Options are set side by side with their conditions while the customer is still in the conversation.
- The challenge:
Long ramp time
Confidence arrives after months of exposure, and leaves when the portfolio changes.
With ClearMash Brain:Shorter ramp for new hires
Product confidence arrives in weeks because it does not depend on accumulated exposure.
- The challenge:
Incomplete AI recommendations
A recommendation engine working from marketing copy recommends what reads well, not what applies.
With ClearMash Brain:More reliable sales AI
Assistants recommend from governed knowledge, with less room to guess.
The pipeline stalls on What and How
What: what this product actually includes, what it excludes, what it costs under these conditions, which version the customer is looking at, and who is eligible for it. How: how to qualify, how to compare, how to position it against the alternative, and how to hand it to delivery without losing the conditions agreed in the room.
Marketing material answers the What persuasively, product documentation answers it precisely, and the How is left to the salesperson. The reconciliation happens in their head, differently each time, or it does not happen and the deal slows.
The same gap limits digital sales. A guided journey or an AI assistant can only recommend as well as the product understanding behind it, which is the same understanding the salesperson needs.
The recommendation arrives with its conditions attached
A position: this option, for this customer, because of these criteria, subject to these conditions.
Product truth, eligibility and conditions sit together, so a salesperson can raise an option they have never sold without hedging, and can compare options in the conversation rather than after it.
Because the same understanding sits behind the portal and the assistant, digital and human channels recommend the same thing. A customer who researched online and then called hears the same recommendation.
When a product changes, the change reaches the field, the website and any AI agent at the same time. The version that was withdrawn stops being sold on the day it was withdrawn.
Eligibility before the promise
Whether this customer qualifies is part of the recommendation from the start.
Comparison on demand
Differences between options are available in the conversation, in terms the customer cares about.
Legacy products stay answerable
What a customer holds today can be explained even when it has not been sold for years.
One story across channels
Digital, assisted and AI-supported sales work from the same product understanding.
What a deal actually turns on
A salesperson settles each of these first, before promising anything.
- WHATWhat this product covers, and where its limits are.
- WHICHWhich variant fits this customer’s circumstances, and on what grounds.
- WHOWho is eligible, and what evidence to hold before committing.
- WHENWhen the current pricing or promotion expires.
- WHEREWhere it is offered on these terms, and where the terms differ.
- WHYWhy to recommend it over the obvious alternative.
- HOWHow to move from agreement to onboarding without losing the conditions.
Does the tier cover the subsidiary, and does the offer still apply next month?
Answered in the meeting, with the conditions stated.
Offers that could apply to this deal, side by side: the conditions of each arrive from the Brain, the expired promotion is replaced by the one running now, and the offer that applies is chosen with the reason stated, in the meeting.
What Products · Conditions · Eligibility
- Price book
- Promotion 2026
- Product terms
- Exclusions
- Bundle rules
- Eligibility
- Discount limit
- Contract terms
- Where offered
- Handover terms
- Renewal terms
How Qualify · Compare · Position
- Qualification
- Fit check
- Comparison
- Positioning
- Quote steps
- Approval path
- Objection reply
- Proposal build
- Handover steps
- AI agent skill
- Sign-off check
Context Decides which What and which How to act on, for this deal
- Who This customer
- When Offer window
- Where Market
- Which Variant
- Why Why this one
- Salespeopleanswer in the meeting
- Customersone story on every channel
- Digital and AIrecommend on governed truth
- The reason is kept on file
In the meeting, when the hard question lands
A prospect asks whether the tier they are considering covers their subsidiary in another market, and whether the current promotion still applies if they sign next month. Each has an exact answer, held in the conditions behind the offer.
Promising to check costs the momentum in the room and days of internal messages. With a Brain the salesperson answers in the meeting, with the conditions stated, and the proposal that follows carries the conditions agreed in the room.
Where a Brain sits between the catalog and the conversation
The pricing system knows what a product costs. The Brain knows what it means for this customer.
Your CRM keeps the opportunity and your pricing system keeps the price. The Brain sits on top of both, and what it reads behind a recommendation is what a seller currently reconciles alone: what is offered today and in which variant, what this prospect already holds, who qualifies and on what evidence, and what the organization has already promised in public.
Where recommendations land is why the same answer reaches the buyer whichever door they came through. It sits beside the opportunity, carries into the proposal, and is what the site and the assistant recommend.
What the Brain reads behind a recommendation
- Product, pricing and packaging systems What is offered today, in which variant, and what was withdrawn.
- CRM and opportunity records Who this prospect is, what they hold, and what has been discussed.
- Eligibility rules, terms and approvals Who qualifies, on what evidence, and what has to be signed off first.
- Marketing and published material What has already been promised in public, so the pitch matches it.
- Quote and configuration rules What can be combined, discounted and approved before a price goes out.
Knowledge orchestration layer
ClearMash Brain
What · How · Context
What this option includes, and who qualifies for it.
Where recommendations land
- The CRM, on the open opportunity The option and its conditions, beside the deal already being worked.
- Proposals and quotations A comparison the customer can read, with the conditions carried in.
- The site and the guided journey The same recommendation online as the one a salesperson would make.
- Sales assistants and AI agents Recommendations built on governed product truth, conditions included.
- The handover into delivery What was agreed, conditions included, reaching the team that delivers.
The CRM keeps the customer. What is added is what the portfolio means.
Salespeople
The confidence to raise an option they have not sold before, with the conditions in front of them.
- Shorter preparation
- Wider portfolio coverage
- Fewer corrections after the fact
- Faster ramp
Customers
Options explained in terms of their situation, consistently, whether they arrive online or by phone.
- Clearer comparison
- Fewer surprises later
- Faster decisions
- Better fit
Digital and AI channels
Recommendation logic built on governed product truth.
- Applicable recommendations
- Eligibility respected
- Consistent with the field
- Updated on the day of change
Tangible impact
The changes a working Brain makes, in the order a sales organization meets them.
Business impact
- Reduction in new employee onboarding 70%
- Increase in employee satisfaction 62%
- Reduction in inquiry handling time 28%
- Increase in customer satisfaction 15%
- Increase in first contact resolution (FCR) 40%
- Increase in self-service adoption 30%
- Reduction in expert escalations 65%
- Reduction in compliance violations 14%
Technological impact
- AI agent accuracy from 85% to 97%
- Increase in AI agent speed 25%
- Reduction in AI costs 74%
Additional measures
The same impact, read through the measures a sales organization already keeps:
- Ramp time to first independent deal
- portfolio breadth per seller
- proposal correction rate
- cross-sell attach rate
- cycle time from qualification to agreement
- digital and assisted recommendations that agree
These come off the CRM and the proposal history rather than out of a new report, which is what makes them worth agreeing on at the start of a deployment.
Complex portfolios gain the most
A simple catalog lives comfortably in institutional memory. A large catalog of conditioned products is where sellers narrow to a familiar subset, and where a Brain widens the range again.
Judgment stays with the salesperson, for the part of selling that needs it; the facts come from the Brain.
In practice the first area is narrow: a family of products, the conditions that generate the most questions and the eligibility rules that matter most. The same pattern then carries across the rest of the catalog.
Why ClearMash for sales
ClearMash is responsible for the product understanding underneath: that it is correct, current and applicable to this customer.
It improves that understanding and serves it to the salesperson, the portal and the AI assistant at once, so the customer hears the same answer whichever door they came through.
Trustworthy before it is persuasive
What a seller quotes has been approved by the people who own the product, and a withdrawn version is marked as history rather than deleted. Your CRM keeps the customer; the Brain adds what the portfolio means. Security practice and certifications are on the Security page.
See a recommendation that carries its conditions
Book a demo and we will show you eligibility, variant and what a customer already holds arriving together, beside the opportunity and inside the proposal.
Prefer to start with the numbers? The impact estimator works them out