Automated POS advisory for

salespeople

Challenge

Salespeople face two common struggles: Prioritizing which products to recommend, and understanding when to reach out to customers. Despite this, less than 40% of companies adopt some type of AI-powered next best action model. This means that lots of time is being wasted, and lots of new revenue is being left on the table.

Solution

Using advanced transaction analytics and machine learning, we can create detailed customer profiles and continuously detect relevant client events to build an automated recommendation engine to drive targeted campaigns. Current models have seen a 2.5x conversion rate uplift compared to control groups.

Learn more

Key modules

1. Customer Profiling

  • We help your salespeople learn their customers’ situation and financial context in 20 seconds to personalize their approach to their every single customer.
  • Our algorithms continuously identify 50+ relevant client events so that your sales people approach their clients at the right time - for example, upon receipt of a bonus, start of a house remodelling project, opening and account at a different bank, change in family status, etc.
  • Identified client events and characteristics can also feed into and enhance your proprietary propensity-to-buy models and recommendation engines.

2. Products Purchased

  • Via deep localization of transaction classification for each market we detect which products end-users have purchased from both you and your competitors.
  • Your salespeople are provided with a thorough understanding of their client’s product portfolio, which they can use to increase your share of wallet.
  • Ultimately, you can recommend financial products to your clients based on what’s right for them given their overall financial situation.

3. Automated advisory

  • Every salesperson gets a set of prioritized and actionable recommendations as to what action he/she needs to take to address clients’ needs.
  • The recommendation logic is designed to optimize clients’ financial wellbeing, as well as meet their specific needs like financing a home renovation.
  • To prioritize recommendations, we deploy our propensity-to-buy machine learning models which continuously learn from client feedback.

What we offer

A proven data feed and API

that provides next best actions to your platform based on customer transaction data.

SERVICES

industries

media

Join our team

PRIVACY POLICY

Facebook-f
Twitter
Instagram
Linkedin