Pets at Home are the UK’s leading pet care business, providing pet owners with everything they need to be able to look after their pet – from food, toys and bedding, and grooming services, right the way through to the first opinion veterinary care.

Summary

Pets at Home, the UK’s leading pet care business, chose Infoshare+ as their technology partner to create an accurate single customer view, kept up to date in real time. Infoshare+ brought together their customer data from across their entire brand ecosystem; from online and in-store purchases, VIP customer loyalty programme, Vets for Pets, the Groom Room and more. As a result, Pets at Home has now taken a huge step towards a complete understanding of their customers and their pet needs. This has meant they can provide the customer with a more consistent and tailored experience and achieve their wider business objective of using their data to better support their customers. It has also given them the strong data foundation they required to create intelligent and trusted analytical insights and use machine learning and AI to further their progress into better understanding their customers’ needs.

Situation

Pets at Home are always striving to use data to better serve their customers. To realise this ambition, they wanted to use their data more intelligently to better understand their customers, improve the customer experience and make better, more customer-focused decisions. They created a high calibre and agile central analytics team, led by Chief Data Officer Robert Kent, to help the business build a competitive advantage through analytics and insight.

The team’s priority was the development of a new universal analytics platform to deliver the insights needed to understand their customers and their pet care needs. However, fundamental to achieving intelligent, actionable insight is a strong data foundation of accurate, complete and trusted data; one that is available to all relevant departments who rely on the data to make decisions. To create their data foundation, Pets at Home knew they needed to remove the data silos and join up their data from across the business and its’ various ecosystems.

Solution

Pets at Home chose a cloud-based solution, as they wanted their data to be in a scalable and cost effective platform and needed an analytics engine to run sophisticated queries and algorithms in an affordable way. Due to the complexity of the project, they used specialist technology and delivery partners to work alongside the internal business and project teams. Partner suppliers selected, as experts in their fields to deliver each part of the project, were the following:

ClearCore software solution

Infoshare+’s ClearCore software solution was chosen to provide a live single view of Pets at Home’s customers (SCV) and a single view of their pets across product and services by linking data held across their ecosystem.

Salesforce Marketing Cloud

Salesforce Marketing Cloud was selected as a platform for analytical driven CRM / marketing, including making SCV available across the organisation.

Tableau

Tableau created the analytics engine and built dashboards to enable data visualisation.

Datatonic

Datatonic provided the building of a Google Cloud Platform (GCP), data warehouse design and the orchestration of system-to-system data flows.

Creating the SCV

The customer data across the Pets at Home Group comes from several different and often entirely separate sources, both digital and traditional in nature; customers have touch points with Pets at Home across in-store purchases, online, Vets4Pets, the Groom Room, VIPs, Digital and marketing campaigns. As a result, they had millions of customer records from over 20 different data sources; there were over 5 million VIPs alone, who were using their loyalty card on average, on 70% of purchases. They wanted to view all touch points in one place to get a complete understanding of their pet needs and relationship with Pets at Home.

Because the data from across the multiple sources was in different forms and formats, the systems were incompatible, and the customer identifiers varied from source to source, they needed to match people and pets across different rules and data attributes. They selected Infoshare+’s powerful and rigorous evidence-based data matching software ClearCore to link personal and pet information from across all sources to deliver their operational single views, meaning all customer touch points could now be viewed in one place. This included customers’ communication consent information, so preference changes with one department could be adhered to by all.

Outcome

Because they now have a complete view of their customers, Pets at Home can, for the first time, truly understand their customers, their pets and their differing needs. This has meant:

A better customer experience and relationship

As every department and Pets at Home brand are now working with the same customer information when interacting with customers, they can deliver a seamless and consistent experience across all touchpoints. Also, they are now able to demonstrate to their customers through their communications and services that they are valued, respected and listened to, which has been a key priority for Pets at Home.

Better customer personalisation

With the ability to understand customers and their pets, they can improve segmentation and offer more personalised, rounded services.

Marketing campaigns have been more effective

Meeting customers’ specific needs by prioritising only the most appropriate crossand up-sell opportunities, has meant better engagement with the less frequent but more tailored communications.

An increase in customer loyalty

Customers are more likely to stay loyal to brands who provide exactly what they need without bombarding them and respect their contact preferences.

Enabling intelligent analytics, machine learning and AI

Like many organisations, using data intelligently, and using ML/AI to inform customer strategy has been a priority for Pets at Home. However, the insights gained from such initiatives are only as reliable as the data that goes in. By focusing on creating a strong, accurate data foundation that is kept up to date in real time, they have improved the reliability of intelligent insights and the success of ML/AI initiatives.