Advanced Analytics

Identify growth opportunities

Through a combination of data enrichment, descriptive and predictive analytics, identify patterns in your data resulting in more effective communication with your customers and improved marketing efficiency.

Random distribution of target circles in grey with some in blue

Make data accessible

Taking previously inaccessible data and making it available for all teams to access, manage and explore.

Trust your data

Have confidence in what your data is telling you. No more gut feeling actions.

Single view of the customer

Bring together all associated data into one location to create a unified single record for each of your customers.

No long set up times

Have your data flowing in a matter of days through self-serve and supported onboarding, savings thousands in set up costs and maintenance.

Data Enrichment

Broaden your knowledge of who your customers are, enabling insight such as lifestyle, affluence, age group, and demographics.

Metrics

Income
Lifestyle make up
Demographics
Family size
Age groups

Plus many more

Insights

Geographical hierarchy grouping
Profile by supergroup
Affluence purchase behaviour
Identify similar audience groups
Current audience profiles

Plus many more

Recency Frequency Monetary matrix graphic showing ten different categories customers can fit into

Descriptive Analytics

Understand what has already happened in your organisation to describe past performance.

RFM

Analyse customer value using segmentation based on individual purchasing behaviours; recency, frequency, monetary (value).

KPI Trees

Pinpoint issues and highlight success based on a decomposition of your sales into their most basic components.

Marketing Attribution

Use first touch, last touch or multi-source attribution to understand where you're acquiring customers.

Predictive Analytics

Use all your customer information to predict their behaviour – enabling targeted campaigns and accurate forecasting.

Forecasting

Estimate future company performance or customer behaviour over a given time period, such as sales, customer sales value, demand, and stock volume.

Clustering Segmentation

Group customers who would not usually be linked to surface hidden trends and common behaviours in your data.

Propensity modelling

Predict the likelihood that customers behave in a certain way based on their previous actions.

How likely is a customer going to purchase in the nest 7 days?
How much is a customer likely to spend?
How likely is it a customer will churn?

Plus much more

Recommendation Engine

Create a personalised experience for your customers by recommending products that fit their behavioural purchase patterns, without bombarding them with the same item over and over again or with products too similar to previous purchases.

Diagram showing an audience segment made up of the following criteria: family lifestyle, propensity to buy more than 75%, lives in Yorkshire, and in the promising category in RFM. 1,036 profiles match this criteria

Unlock your data value