HubSpot & CRM
Most scoring models are invented in a meeting. Job title worth ten points, pricing page visit worth five, because those numbers felt right. A model built from which leads actually closed usually disagrees with the invented one on almost every weighting.
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Support@adnika.comPartners & recognition
The platforms we build and run campaigns in, and the clients whose numbers we publish with their names on. HubSpot is the one partnership we claim; the rest are tools we use, not badges.
The problem
Marketing built the model, sales does not trust it, and everyone works the newest lead instead of the best one. The score exists, it is displayed on every record, and it changes nobody's behaviour.
Why scoring models fail
Nobody checked which attributes actually correlate with closing. Job title is frequently a much weaker predictor than people assume, and a single specific page visit is often far stronger.
A score handed to a team that had no part in building it is a number on a screen. Reps will work the lead they think is best, and they are frequently right.
Someone who read three pages eight months ago still scores high. Without decay, the score measures history rather than intent.
The model was built two years ago against a different product and a different market. Nobody has checked since whether high scores still close better than low ones.
What is included
Built from data, agreed with sales, and checked afterwards.
What did the leads that actually became customers have in common — firmographics, source, behaviour, speed of response. This is the foundation and it is what makes the model defensible to sales.
Two dimensions, not one number. A perfect-fit company doing nothing needs a different action from a poor-fit company reading everything, and a single blended score hides both.
Students, job seekers, competitors, free email domains where they matter, existing customers. Removing noise usually improves a model more than adding signals.
Scores that fall as behaviour ages, so the number reflects current intent rather than an accumulated history.
What score means a rep must act, and how fast. Agreed with the people who will act on it, or it will not be acted on.
What happens automatically when a lead crosses a threshold. A score with no action attached is a decoration.
After a quarter, do high-scoring leads actually close at a better rate. If not, the model is wrong and gets rebuilt rather than defended.
Some platforms offer model-driven scoring that needs a meaningful volume of closed deals to work. We will tell you honestly whether you have enough data for it to mean anything.
Technology
Your existing platform. This is a modelling job rather than a tooling one.
Where the score lives.
What the model is built from.
Because a score must trigger something.
Quarterly, honestly.
How we work
Analyse, agree, build, then check whether it predicts anything.
Every closed-won deal from the last period, and what those leads had in common. Compared against closed-lost, because a signal present in both predicts nothing.
The attributes, the weightings and the thresholds, reviewed with the people who will act on the score. Where sales disagrees strongly with the data, that is worth investigating rather than overruling.
Scores that decline with inactivity, negative scoring for the segments you do not sell to, and routing that fires automatically at the threshold.
Do high-scoring leads close better than low-scoring ones. If the answer is no, the model is wrong. We rebuild it rather than explaining why the data is unusual.
Why us
Because it is built from evidence and agreed with the people who have to use it.
Not from a workshop. The attributes that actually predict closing regularly disagree with the ones everyone assumed, and job title is the most common casualty.
A score sales did not help build is a number they will ignore, however good the model is.
After a quarter we check whether high scores close better. If they do not, we say so. A scoring model that does not predict is worse than none because it misdirects effort.
Interest ages. A score with no decay measures what someone did last year rather than what they are doing now.
Industries
Every number below is the count of case studies we have actually published in that sector, and the best result among them. Nothing is a counter.
Selected work
:quality(80))
Two disconnected websites rebuilt as one bilingual WordPress site with a HubSpot funnel behind it.
:quality(80))
Seventy-two treatment pages in Dubai’s most contested clinical category, built inside DHA advertising rules.
:quality(80))
One site carrying aesthetics, dentistry and surgery — three audiences, three routes, one design system.
:quality(80))
A Dubai property platform with filterable listing search, a map of the city and a mortgage tool.
:quality(80))
A scroll-scrubbed WebGL scene experience spanning six divisions — and still a PageSpeed of 90.
:quality(80))
Office furniture on Shopify, serving a single-chair buyer and a corporate fit-out from one catalogue.
:quality(80))
A smart-lock catalogue with parallel routes by product, by industry and straight to the flagship.
Where this sits
Scoring feeds the routing and automation elsewhere in this hub.
Client stories
On camera and in writing — swipe through the founders and teams we’ve helped design, build and grow.
In their words
GMC is thrilled to extend our heartfelt appreciation to Adnika! Collaborating with Ehsan and his team has consistently been an absolute delight. Ehsan's dedication and commitment have ensured that German Medical Center remains an exceedingly satisfied and happy client, especially regarding their Hubspot Onboarding, Digital Marketing, Website Development, Content Creation and Social Media Marketing. Adnika is indeed the Best Digital and Growth Marketing Agency in UAE!
Adnika provided us with their Inbound Sales and Marketing solutions through Hubspot. They helped us generate more qualified leads for our sales team, drive website traffic, increase customer engagement, and grow our customer base. Adnika is a reliable partner that has always taken our specific goals and needs seriously.
Adnika has helped us plan, implement and optimize ad campaigns on Facebook and Instagram. Adnika is truly committed to Performance Marketing. They provided us with a fantastic dashboard with detailed KPIs that helped us track the campaigns’ performance in real time. Adnika also gave us helpful and dedicated support during the whole project, and the campaigns turned out to be a great success. We highly recommend working with Adnika's growth experts.
We really enjoyed working with Adnika’s team. Not only are they talented, but they all take the time to understand whom they're working with, what they're trying to accomplish, and how to help the business achieve its goals. The quality of work we've experienced has made a huge difference for us and helped drive new business.
Adnika helped Sea Technology with setting up new digital channels, such as Google Search Ads, to attract more customers and leverage our brand. We are very satisfied with the results and we will continue with the implementation of lead generation, marketing automation, and performance marketing.
Working with the Adnika team has been a real pleasure! Extremely friendly, Ehsan and Elin are always available with prompt replies, valuable insights, patience, a problem-solving attitude, and high knowledge. Super easy to work with them. I highly recommend the Adnika team to help your business!
I am an artist, but I also manage a collective of DJs. In order to promote our services to our clients, we needed Inbound solutions that could attract the right traffic and promote the brand. Adnika built and designed our Inbound processes as well as create and manage campaigns on social media and Google Ads which helped us attract many more customers. I’m very happy!
We've been using Adnika growth marketing solutions only for a few months. They are highly professional, competent, experienced, and creative. Get ready to get to work with this agency. They will come alongside you as a business owner and feel your pain and joy! Get ready to transform your business.
Questions
Starting with what this search term actually returns.
AED 9,000 to AED 45,000 covers most of what we are asked to build. The number moves on how much historical data there is to analyse, whether fit and engagement models are both built, whether routing and alerting are in scope, and whether ongoing quarterly validation is included. Anything quoted before those are known is a guess. We scope first, then price, and the scope document is yours whether or not you proceed. These are market ranges rather than a fixed rate card — the proposal carries the real figure.
No, and it is worth being clear because the term is misleading. That first page is Gumloop's seven best tools, HubSpot's product page, ZoomInfo's ten tools compared and several similar. Everyone searching it is shopping for software. You almost certainly already have scoring capability inside the CRM you own — what is usually missing is the model, which is what this page is about.
Assigning a number to each lead that estimates how likely they are to become a customer, so the sales team works the best ones first. The number comes from two things: how well the company fits what you sell, and what that person has actually done.
A B2B software company might score a lead higher for being in a target industry with over fifty staff, higher again for visiting the pricing page twice in a week, higher again for requesting a demo, and lower for using a free email address or for having gone quiet for sixty days. The rep sees a number and works the top of the list.
Grading usually describes fit — is this the kind of company we sell to, often expressed as A to D. Scoring usually describes engagement — how much interest have they shown, expressed as points. The distinction matters because they need different responses, and collapsing them into a single number is the most common modelling error we find.
You need a reasonable number of closed deals for the analysis to mean anything. Below roughly fifty closed-won in a comparable period, the patterns are not reliable and we would recommend simple routing rules instead and revisiting later. We will tell you which case you are in before quoting.
By comparing closed-won against closed-lost and seeing which attributes actually differ. A signal that appears equally in both predicts nothing regardless of how sensible it seems. Then we review the result with sales, because they sometimes know something the data does not show.
Three to five weeks including the analysis, the review with sales and the build. The validation happens a quarter later and is part of the engagement rather than an extra.
High-scoring leads should close at a materially better rate than low-scoring ones. We measure that after a quarter. If they do not, the model is wrong and we rebuild it.
Then either the model is not predicting or the threshold action is not built. Both are fixable and both are our problem rather than a discipline issue. Usually it is that crossing the threshold does not actually create a task for anyone.
If you have the volume, it can outperform a rules-based model. It also needs enough closed deals to learn from and it is harder to explain to a sales team, which affects trust. For most Dubai mid-market companies a well-built rules model is the better starting point.
No questions match — try another search.
Next step
Most companies have never checked. Send us last year's closed-won deals and we will tell you which signals genuinely predict a sale.
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