Loyalty Use Case

Helping loyalty & CRM teams build high value customers

ROI: return of $1.2M per annum (26X ROI) for a group of 40 product, CRM & loyalty managers.

Using AI to provide loyalty & CRM teams with faster, more meaningful insights to support customer/member engagement strategies & help them reach their target customers. Anna allowed loyalty & CRM teams obtain a personalised understanding of current & target members/customers, allowing accurate targeting by customers with similar purchase or spending patterns.

Problems we were tasked to solve and audience

Helping loyalty & CRM teams:

  • 1.Enabling teams to understand customer & member behaviour in detail, allowing accurate targeting by customers with similar purchase or spending patterns.
  • 2.Developing strategies to define, manage & maintain different tiers of membership, building engagement & loyalty.
  • Frequently used terms:

  • Customer profiling / targeting / segmentation
  • Brand loyalty
  • Purchasing Behaviour
  • Customer retention
  • CRM
  • Customer lifetime value
  • Audience

  • CRM / Customer acquisition / loyalty / retention teams
  • Data

  • 2 years of data, each row representing a customer snapshot (at a point in time) or transaction (by date)
  • Ability to profile by demographics (e.g. age, gender, household, postcode), tenure (new/lapsed customer flag), purchasing behaviour (e.g. product / brand mix, transaction amount/quantity) & membership/loyalty segments (e.g. status, points, preferences).
  • Result delivered - sample questions

    Sample Questions

  • 1.NEW MEMBER GROWTH - Anna, show me the number of new members last quarter
  • 2.CUSTOMER PROFILING - Anna, show me the customer profiles of all new members, by demographics, spend & product preferences
  • 3.MEMBERSHIP / TIER MANAGEMENT - Anna, how many female aged 25-30 members upgraded from silver to gold last month?
  • Summary of value


    Marketing, product & brand managers must build business cases to justify the cost & direction for new product or communication decisions. Before Anna, the process of gathering the required data and insights was estimated to take an average of 5 business days (40 hours) to build an accurate understanding of customer profiles & behaviours per each business case - with business cases often built of quarterly, 6 monthly or annual planning cycles.

    After the implementation of Anna - this was reduced to 2 hours - saving 38 hours per business case (approximately 1 week per business case). Across a team of 40 product & loyalty managers, this equated to a time-saving worth over $1.2M per annum (26X ROI) for a group of 40 managers in the pilot group building a quarterly business case, each additional business cases saving even more cost & time!

    Summary of value

  • CUSTOMER ACQUISITION - Teams can come up with a highly relevant strategy to attract new customers by identifying from new/existing purchase behaviour, product preferences, segment movement, etc.
  • MEMBER TRENDS + NEW PRODUCTS / CAMPAIGNS - Teams can identify the latest trends by analysing members reaction to different new product or campaign, by customer groups/segments
  • Screenshots

    Pro-active insights

    Tasks such as creating your own reports or dashboards require the knowledge of where to navigate through your data for insights, but this has been proven difficult and time consuming.

    Using the power of AI, Hyper Anna executes millions of hypotheses to discover complex patterns in datasets. The most practical and relevant insights are then pro-actively delivered to your inbox. In contrast to large teams of analysts finding answers from data, Hyper Anna will single- handily do it in a matter of hours.

    In this example below, Hyper Anna automatically suggests a loyalty manager to look at brands or categories that are under- or over-performing significantly, and importantly, the factors that contributed to this.

    Ask anything

    Getting insights from data is now as simple as asking a question.

  • Surpass the “create vs. consume” dichotomy of reports and dashboards by giving all users access to a self serve platform
  • Govern your data centrally but democratise access to all
  • In this example below, a loyalty manager has asked Anna to analyse the revenue performance by membership.