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Quantified and shared goals
committed on ROI
Continuous optimization

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Solution for business
Usable without data experts
Specialised by activity

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Turnkey project
Business Interlocutors
Support on run


Limit your attrition rate and stop losing customers to your competitors

Customer churn, that is customers defecting to the competition, is a growing phenomenon. This greater volatility, combined with existing legislation regulating competition, means businesses have to reinforce their loyalty initiatives. If these actions are going to be truly efficient, they need to be fine-tuned and carefully targeted.

AfterData’s software solution identifies customers who exhibit the weakest churn signals, by analyzing their behavior: web browsing; consumption patterns; their interactions with the sales department; their openness to competing offers; etc.

Thanks to AfterData’s proprietary algorithms, “anti-churn” measures can yield significant ROI, enabling businesses to identify between 70% and 85% of customers who are likely to churn.

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Maximize the efficacy of your promotional offers

In distribution, promotional products represent an increasing share of companies’ overall sales volume, accounting for up to 30% for certain sectors. These one-off operations often go hand in hand with risks of stockout and overproduction. The quality and accuracy of sales forecasts has a direct impact on companies' results.

With AfterData, you can optimize the product / price / promotion mix and effectively anticipate what quantities need to be produced or ordered. These forecasts are based, in particular, on the history of promotions, baseline products assortment, national agreements, etc.

AfterData can yield an impressive ROI, reducing your forecasting errors by 20%, unsold inventory by 30%, and increasing your promotional volumes by 30%.

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Fine tune your customer categories and improve your targeting

In a context where the cost of customer acquisition and retention is ever increasing, it is essential to maximize the knowledge you have on prospects and customers.

AfterData’s proprietary solution identifies high-potential prospects, as well as enabling you to anticipate the future needs of active customers.

This enhanced segmentation is based on our machine learning algorithms applied to your data: customers’ browsing history on your website; their interactions with your customer service and sales services; their household profile; past consumption patterns; etc.

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Maximize sales staff presence at a point of sale or restaurant

For all businesses, the largest expenditure is usually the payroll. The number of customers attending a point of sale or visiting a restaurant can vary greatly from one day to another. The sales force actually present determines both sales levels and customer satisfaction.

AfterData’s software solution can predict the level of customer attendance and optimize the workforce required to support the commercial activity effectively. These predictions are built on past sales history, market trends, weather impacts, local activity, etc.

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How to optimize the sales force of a point of sale or a restaurant?

The payroll is usually the first expense of a trade. The flow of customers into a point of sale or a restaurant is very variable. The current sales force determines the level of sales and customer satisfaction.

AfterData solution is used to forecast the level of customer traffic and to optimize the workforce required for commercial activity. These forecasts are made thanks to sales history, market trends, weather impacts, local activity ...

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Automatically detect suspicious behavior

The digitalization of the economy, makes for the rapid, and even automatic handling of customer records in the fields of banking, insurance, e-commerce, etc. This speed of processing makes it very difficult to detect potential frauds.

The neural networks of AfterData’s software detect presumptive fraud in real time to block operations before suffering the consequences of potential deceit.

Unlock a significant ROI, detecting up to 40% to 75% of frauds

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Adapt staffing and staffing location to match needs

The very essence of emergency-response services (police, fire brigade, hospital EA units, etc.) means they have very irregular activity. Therefore, it is vital to align the distribution of resources as closely as possible to the risk in order to optimize the timeliness and the quality of the operational response.

AfterData’s machine learning algorithms analyze past operations, and determine causal factors to predict both how many emergency interventions to expect and where they are liable to be needed.

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