A data-driven sales approach using AI - A&M use case
Ask any sales representative what they dread most, and chances are high that ‘cold calling’ tops their list. Instead of relying on gut feeling, use AI to rank prospects by likelihood to buy – and focus on only the most promising potential customers.
Getting rid of dirty data with AI– Coca-Cola use case
Customer data is collected in various ways with(out) standard data collection forms and collected in various places. But when consolidating the data, you’ll notice duplicates, inaccuracies and incompleteness – in other words ‘dirty’ data. Enter AI.
Why customers are really buying – Esko use case
Imagine that you can recommend your customer to buy a bike carrier, because look-a-like buyers with tow bars are very likely to bike. Using AI, you can go one step further with upselling tactics by recommending non-evident products.
Match communication with customer behavior - Terumo use case
How recent is the last purchase? How often do they buy? How much do they spend? By clustering your audience using AI and engaging them in a well-segmented marketing campaign, you are able to create a personalized offer for a high-value customer.
Supercharge customer segmentation – Q-Park use case
When you add AI to customer segmentation data, you’ll generate superior results compared to traditional analytics-driven marketing campaigns. Your customer targeting becomes more accurate, dynamic and capable of boosting conversions.
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