3 Ways Machine Learning Tools Can Drive Sales Over the Holidays

While getting ready for Black Friday and Christmas shopping season, leading retailers attempt to predict the hottest trends, define reasonable prices and foresee a time-slot an average consumer will spend on a particular product. With big data analytics and powerful machine learning tools, their predictions can be the most accurate.

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1. Added Customer Support

According to Salesforce’s Adam Lawson, customer experience is the most important variable separating successful and unsuccessful sales teams. ML will allow for significant improvements to customer experience — with the ability to proactively follow up with leads, customize the user’s experience and answer questions via chat (called chatbots), every customer will have an experience tailored to their preferences and needs.

2. Improved Forecasting

Within the last few year, advanced lead scoring has become an extremely popular tool for sales teams. Lead scoring, which uses ML, looks at collected data on prospects, such as their budget, size, past sales, and interaction with marketing emails then formulates a score which will project interest and the likelihood of a sale. This process reduces the number of dead leads and focuses a sales team on converting strong leads to clients.

3. Personalized Suggestions

In the retail industry, you may have noticed the text “other customers purchased” or “you may also be interested in,” followed by a list of similar or complementary products. These suggestions are thanks to ML, which allows supporting a consumer-centric approach, through the analysis of sales patterns, purchase histories, and data consumption. Companies like Amazon, Spotify, and Netflix are already employing this solution to suggest additional content for customers. As this technology becomes more readily available, smaller retailers and SaaS companies will begin to follow suit.

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