When we talk about recovering or avoiding lost sales in real time in a webshop (also largely applicable to calls received in a call center), we’re referring to the ability to identify and act on sales opportunities that are about to be lost. This way, if a potential customer shows interest and there’s any sign that the sale might not be closed, the system or team can immediately intervene to try to save that opportunity, leveraging information as it happens.
Real-time recovery seeks to be proactive and dynamic, allowing for instant responses to customer signals or behaviors. Several technologies and strategies exist to achieve this:
Hybrid search engines: These search engines not only query the internal database, but can also access external sources, such as other knowledge databases, supplier databases, etc., thereby improving search results.
Third-party suppliers: This involves establishing agreements with suppliers so that we can use third-party stocks in real time for fast deliveries and thus expand our service level capabilities.
Related products: This involves automatically suggesting alternative options when a product is unavailable to maintain customer interest. This strategy is actually of little use in automotive parts, as customers aren’t interested in purchasing “other” products, but rather the exact one they’re looking for.
Chatbots and Virtual Assistants: These are specific tools that interact directly with customers in real time with conversational capabilities, offering immediate attention, resolving questions, or helping close sales.
Marketing automation: This involves sending messages, offers, or personalized assistance immediately after a potential purchase has been abandoned. This would be our last resort in trying to close the sale, focusing on communication and customer relationship management by automating marketing and sales tasks.
To differentiate these strategies, which act in real time, from others that act at other times, we can mention:
Preventive strategies: We try to prevent the problem before it occurs, such as by building customer loyalty.
Proactive strategies: We strive to not only prevent but also anticipate potential problems dynamically, for example: demand analysis to optimize product range, competitor price analysis, purchasing process optimization, sales team training, etc.
Post-strategies: These are based on historical data analysis, for example: analysis of stock availability displayed at the exact time of the query, analysis of non-competitive prices displayed, etc.
Typically, non real time strategies, consist of reviewing historical data to understand what happened, why the opportunity was missed, and what could be improved in the future. It’s a more reflective process based on past analysis, which helps us learn and adjust data and strategies, but it doesn’t allow us to act at the exact moment an opportunity arises.
Anyway, many of the strategies we’ve discussed, both those that operate in real time and at other times, use Artificial Intelligence and Machine Learning, which actually act as an artificial brain.
Furthermore, all these different technologies and strategies must work in conjunction with our CRM and/or ERP to share information instantly and automatically, synchronizing all data, thereby achieving much more effective sales and real-time sales recovery.
NEO system is a solution developed by Factory Data based on artificial intelligence, which provides hybrid search functionalities for the discovery of equivalencies in real time and also demand analysis to optimize the product range for the discovery of new opportunities, analysis of availability levels and potential non-competitive prices, in short, multiple crucial strategies to analyze and minimize lost sales in our company.
