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Case Study

Unbxd Running Efficient Forecast Calls

Saahil Dhaka
Saahil Dhaka,CEO at Clientell
3 mins read
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About Unbxd

Unbxd is a San Franciso-based, leading e-commerce product discovery platform that applies advanced data sciences to connect shoppers to the products they are most likely to buy while providing predictive, actionable insights for merchandising.

To explain this in further simple terms, let's take an example:

Merchant X puts up their products on a specific E-commerce platform after registering. For them, the most important thing is visibility and knowing whether they are shown to the right audience.

Unbxd uses AI to do this. Using trends, demographic data, pricing, gender, and other filters and parameters historically for a particular segment or product, Ubxd ascertains which audience it should be shown to.

This results in more significant sales and success for the merchant.

Forecasting and Unbxd

Even though Unbxd built software to tell its customers with certainty what was best for their products and where they should show, they needed to be more certain about their own sales deals with their potential opportunities.

Their forecasts needed higher accuracy. Why? You guessed it. Their data needed to be completed because it took significant time to fill in salesforce, which reps avoided doing.

With Clientell’s automated activity and contact data capture from the rep’s sources(email inbox, calendar, and other integrations), the data entry process became much easier, and the data layer was sorted to forecast further.

Now Salesforce’s forecasting was not effective for Unbxd at all. The process was limited to senior management submitting just “numbers.”

Clientell brought ease and inclusivity into this process. It gave Unbxd the use of critical features such as pacing, nth-day analysis, and leveraging historical data using AI. Let's explore these and see how they helped Unbxd.


With pacing, Unbxd could see where their reps stood in real time with respect to their targets. This would help them re-allot deals and targets, depending on what reps seemed capable of after a certain amount of time had passed.

It also helped them see with what speed they’re able to achieve targets overall, and depending on that, they could change their forecast numbers. If they were achieving targets faster than expected, they could increase their forecast and add more deals, or if they were lagging, they’d do the opposite.

nth-day Analysis

nth-day analysis helped them predict market situations and react faster. They could break down the pipeline by different business units and across different revenue streams, where they stand on a specific day compared to a previous quarter. The analysis would help them understand market trends and outcomes of their investments in marketing and sales efforts.

Historical Data

Finally, Clientell’s AI helps them with insights leveraging historical data. Being in action since 2010, and having smaller teams, Unbxd greatly benefited from this. They could see in real-time, with a couple of clicks, what worked for them and what didn't historically and how they could change accordingly.

With this, Unbxd’s monthly forecasting cadence became refined, and the takeaways were crisp and precise.

Moreover, Clientell adapted their monthly cadence, as cadence frequency on the platform is customizable. Another client, Pixis, with a bigger team, prefers weekly cadences, which can be easily set with a few clicks!

“We’re delighted with what Clientell has done for us. It's a game changer!” said a satisfied Pawan as he went in for his next monthly forecast meeting, much happier, content, and correctly anticipating a sturdy result.

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