9 ways to boost sales with artificial intelligence
← Blog 9 ways to boost sales with artificial intelligence Artificial intelligence, which used to be kept under wraps, is now finding its way into every aspect of marketing and sales. Algorithms are boosting customer knowledge, optimising actions and boosting sales results tenfold. However, in this technological craze, companies must be careful not to fall into a dehumanised approach, since the human factor remains the guarantor of a lasting customer relationship. In this article, discover 9 concrete applications of AI to increase the sales process. As you read on, you’ll learn how these technologies are transforming salespeople’s work to boost results, while reinforcing the human-centric customer approach. 1 – Chatbots Now a must-have AI solution, chatbots automate exchanges with customers on digital channels. Thanks to this technology, the most frequent queries receive an instant response, without requiring the intervention of an agent. The chatbot understands the questions asked thanks to natural language processing (NLP), and responds according to the data in its knowledge base. The most relevant answers have been defined in advance by the marketing and customer service teams. The chatbot then selects the appropriate response based on its analysis of the customer message. This automation of simple, recurring queries offers multiple benefits : Saves time for the customer, who receives an immediate response, 24/7. Reduced workload for customer service teams, who focus on complex requests. Improved customer satisfaction thanks to instant processing. Personalise responses by refining algorithms according to customer profile. Many sectors are now adopting chatbots to improve digital customer relations : In e-commerce, a chatbot on the website informs visitors about products and facilitates the purchasing process. In banking, it interacts with customers via the mobile app to provide account balance or block a card. In telecoms, it notifies users of their consumption or the evolution of their package. In the tourism sector, they chat on social networks to recommend activities or answer practical questions. With chatbots, the customer experience becomes more efficient in many sectors. This AI technology optimises exchanges across all channels for 24/7 accessible customer service. 2 – Highly personalised recommendations Product recommendation algorithms use artificial intelligence to offer each customer the most relevant references according to their tastes. This extreme personalisation boosts sales by facilitating the discovery of new, adapted products. The recommendation engine exploits data such as products already consulted or purchased by the customer. It identifies their preferences and determines which references are likely to interest them, from a vast catalog. AI goes even further, analysing customers’ overall behaviour. It detects correlations between products that would escape the human eye. In this way, the engine is able to suggest items that match the customer’s expectations, even if there is no obvious link with their habits. Fine-tuning recommendations for each customer profile offers multiple advantages: Extremely personalised user experience on the website or app. Easier discovery of relevant new products. Conversion rate boosted by offering references in line with needs. Additional sales by encouraging the purchase of related products. This ultra-personalised recommendation technology is successfully used by Amazon, Netflix and Spotify, among others. Whatever the sector, AI paves the way for tailor-made suggestions for each customer, to increase the average shopping basket. 3 – Predict sales using statistical models AI predictive sales analysis enables accurate estimates of future sales volumes. Statistical models make robust projections based on past data and market trends. These complex mathematical models incorporate multiple parameters. They take into account historical sales over several years to identify trends. New market share gains are also taken into account, as well as the constant evolution of demand and buying behaviour. The impact of seasonality is also taken into account, with sales of certain products fluctuating according to the time of year. Marketing and sales actions planned for the coming months are projected into the estimates. Product launches and discontinuations also influence projections. Finally, the overall economic situation and its repercussions on the business sector are analysed. The combination of all these parameters makes it possible to establish solid forecasts thanks to the power of AI. Accurate sales forecasting offers the following advantages, among others: Anticipate stock-outs and shortages by adjusting production and supply levels. Optimise team sizing to absorb anticipated peaks in activity. Adapt individual and collective objectives to anticipated trends. Allocate marketing and sales budgets to periods of maximum impact. Adjust the supply chain by alerting suppliers to future needs. As you can see, predictive sales analysis using AI improves anticipation in many areas. Companies can look ahead with confidence and optimise their operations accordingly. 4 – Automatically target high-potential customers Automatic targeting algorithms identify the profiles in your customer base most likely to buy your products or services. AI determines the prospects with the best potential to optimise sales actions. The targeting engine exploits the behavioural data collected. It analyses each customer profile in detail: Interactions on the website ; Purchase history ; Reactions to marketing campaigns ; etc. It deduces a propensity score, reflecting the likelihood of purchase or conversion. Profiles with the highest scores are automatically integrated into emailing, social selling or online advertising campaigns. Lower scores are worked on with “churn” algorithms to retain prospects before they leave the site for good, for example. Optimising sales targeting with AI generates multiple benefits. Lead conversion is boosted by targeting mature and advanced profiles in the sales funnel. Sales productivity is boosted as teams focus exclusively on very high-potential leads. Acquisition costs are also reduced, as only relevant prospects are targeted. Thanks to this refined targeting, the conversion rate increases throughout the entire customer journey. Last but not least, ROI on campaigns is significantly improved thanks to the precision of targeting made possible by algorithms. Thanks to automated targeting, teams can concentrate their efforts on high-potential prospects and customers, for greater efficiency. 5 – Segment your customer base finely Intelligent AI segmentation automatically partitions the customer base into homogeneous groups. Each segment presents common characteristics and behaviours. This tailor-made segmentation makes it possible to personalise sales
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