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How to turn data into carrots to attract new customers
To keep growing you need to keep bringing in new customers. Data management can strongly enhance the customer acquisition process. It helps you predict the lifetime value of new customers. You can learn how much prospects are likely to spend by looking at the turnover generated by customers with a similar profile. This analysis enables you to focus on acquiring high-value customers. Moreover, you can exclude low-value customers who drain resources and reduce profitability.
Would you like more advice on this vital matter? We’ll happily help you on your way.
Weeding out bad debtors
In Europe an impressive number of bankruptcies are directly due to late payments or unpaid invoices. Both in B2B and B2C markets it is vital to detect early which customers pose a high risk of bad debt. Powerful data solutions provide scoring models that accurately estimate the risk of customer fraud. Even before the transaction takes place.
Data crossbreeding: detect prospects with top customer potential
Determining who your best clients are, allows you to target their ‘look-a-likes’ as prospects with the highest potential. To identify your best customers, you can rely on e.g. an RFM analysis (measuring the Recency/Frequency/Monetary value of purchases). Once you have scored your best customers, you can build their profile:
The leads that closely resemble your high-value customers are targeted with the highest priority. Improved targeting efficiency allows you to cut marketing costs and to avoid “spray and pray” strategies.
Increase the basket size of existing customers
Acquiring customers is necessary but expensive. Another source of growth is to increase the value of your current customers. Data analytics helps you achieve this. With advanced association methods you can fine-tune targeted upselling and cross-selling offers in real-time. It also optimizes the effectiveness of your marketing resources.
Cross-selling the Amazon way
The simplest cross-selling method begins with ‘if customers buy product A, then propose product B to them, whatever you have available’. But you can achieve much finer results with a careful use of data. Think about ‘next product to buy’ models, which Amazon has put to perfection. Each purchase at Amazon is immediately followed up with highly relevant suggestions, based on loads of retrieved data: history of visits and purchases, time spent on a specific page, last website visited before arriving on Amazon, items added to carts but abandoned, purchase behavior of similar customers, demographic information, etc.
All these criteria are weighed in an elaborated algorithm, which helps Amazon deliver the optimal purchase experience.
Putting customers/data at the root of your strategy
As a highly customer-centric company, Amazon decided years ago to put data at the heart of their strategy. They keep track records of every action taken by their consumers on their website. They transform this flow of information into actionable insights on what exactly customers want. This enables Amazon to suggest the best possible offer to maximize the basket value of each customer. This is the philosophy you should adopt, no matter your sector, your maturity, or whether you sell products online or offline.
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