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Predict Cross-Selling
Identify which items or services existing customers might like to add to their current purchases and increase your revenue stream.
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The Challenge
For long-term growth and success, businesses must generate consistent revenues and high-profit margins. Cross-selling is one way to do this, especially if the company has several complementary products or services.
However, cross-selling has its challenges, even if customer demand is high.
Marketing and sales teams may not have the knowledge to sell many different products to various customer segments. They may be unable to address the correct type of customer poised to purchase a specific product or service.
Furthermore, some customers may not engage with cross-selling strategies, especially if they are not interested in the offered bundles.
How can companies overcome these challenges and arrive at an accurate cross-selling prediction rate?
The Solution
Graphite’s no-code machine learning helps companies identify which products or services their target market will likely purchase.
AI builds a model to help companies predict whether customers will be interested in similar or related products or services. It can then help sales and marketing teams create strategies to leverage this data and increase sales across the board.
Graphite can also help finance teams allocate resources for marketing and sales to focus on strategies that will improve cross-selling rates. They will better understand their target audience and how to market the products that will address their needs.
The Impact
Cross-selling is one of the best ways to market and sell products as it does not involve acquiring new targets or leads. Businesses can increase their revenue by offering their existing customers related or complementary products or services.
With Graphite’s no-code machine learning, companies can more easily identify the best products or services for cross-selling and which customers are best to target. This is all easily accomplished without additional marketing strategies or new channels that incur higher costs.
Further Reading
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