“The partnership between Artefact and Reckitt has been phenomenal and we consider the Artefact team to be part of the Reckitt family.  The people are the key success factor of the Audience Engine; they drive conversations on every step we need to take and engage major stakeholders with professionalism and skill.”
Stanley Wang – Audience Engine Product Owner, Reckitt

Artefact’s data scientists, data engineers and consultants worked with Reckitt’s transformation team to implement a powerful and scalable solution that will enable Reckitt to make intelligent use of data to drive sales effectiveness from its digital marketing activities. Called the Audience Engine, the platform is now used every day by Reckitt’s teams around the world.

CHALLENGE

Transform into a digital-first business and use data effectively to increase sales

Reckitt is a multinational consumer packaged goods (CPG) company, with offices all over the world. Its purpose is to create a cleaner and healthier world and its products include household favourites such as Dettol, Durex, Harpic, Lysol, Nurofen and Vanish.

Like many businesses today, Reckitt recognised that it relied on traditional methods to understand its customers – consumer panels that delivered audience insight based on surveys, brand knowledge, demographics, consumption and market statistics; shoppers were predominantly reached through TV advertising.

Reckitt’s mission was to transform itself into a data-first business, a move that would enable it to exploit the value of its own data to strengthen its understanding of its consumers, and from there make its digital advertising more effective in order to increase sales.

“We know the world has changed; we want to use our data more effectively to drive increased sales.”
Stanley Wang – Audience Engine Product Owner, Reckitt

SOLUTION

The Artefact Audience Engine: machine learning and AI models turn data into actionable insight

The Artefact Audience Engine takes a scalable and artificial intelligence (AI)-driven approach to first-party data.

Looking at the user journey (on its websites) provides Reckitt with insight about the user’s intentions, and their propensity to purchase. Artefact’s custom built machine learning models use this data to create hyper-targeted audiences for digital marketing campaigns. These audiences are built and sent directly to a demand side platform (DSP) of choice through API connections and are used as seed segments for DSP lookalike models to find scale. The Audience Engine allows the brands to answer their specific business questions, better understand their customers, and target them according to their needs.

One of the very few Google partners to be certified on both the Google Cloud Platform (GCP) and Google Marketing Platform (GMP), Artefact used both platforms to build the Reckitt Audience Engine.

“Leveraging the GCP and the GMP at the same time allows us to move data into an environment where we can apply our machine learning and artificial intelligence models and then push it directly back onto the GMP platforms for insights and activations.”
Derek Li – Senior Data Consultant, Artefact

The Audience Engine helps Reckitt’s brand marketers deliver campaigns that are more effective at reaching core consumers.  But the benefits also extend across the business: the media team is able to create more efficient media campaigns; communication strategists can better understand audience performance and use this to prioritise future business objectives and activities; while the CRM team is able to build stronger programmes and content.

DEPLOYMENT

Multi-disciplinary teams roll out and scale the Audience Engine across Reckitt’s global business

Artefact worked with Reckitt’s transformation office to deploy the Audience Engine at a global level.  Data scientists developed the product in terms of its capabilities and algorithms; consultants rolled it out to all the markets and brands; and data engineers worked to industrialise the tool, building a platform so that anyone from Reckitt can run the Audience Engine for any brands automatically.  This took place in four streams, with a robust project management methodology implemented by Artefact to deliver a programme of this scale:

  • The rollout team worked directly with the martech leads, the media managers and the brands to deploy the tool.

  • The product innovation team, made up of data scientists and consultants, listened to the needs of the business and developed new capabilities for the Audience Engine that enabled these to be resolved.

  • The product industrialization team worked to scale the product, developing a tool so that the Audience Engine runs automatically.

  • The adoption team demonstrated the value of the Audience Engine to the broader business, consolidating results and talking to different stakeholders about how it could help them in their own day-to-day tasks.

“We needed a very strong mix of data scientists, data engineers and consultants to deliver what Reckitt was expecting from the Audience Engine.  The roll out has demonstrated increases in both efficiency and effectiveness across all markets, and we are now focusing on product innovation with the team at Reckitt.”
Manuela Mesa – Consulting Manager, Artefact

RESULTS

Test and learn campaigns show 30% increase in media spend ROI

Reckitt has big ambitions for its Audience Engine, wanting to ensure it will be used across all key brands and markets.  To achieve this, it adopted a methodical approach, first creating digital centres of excellence in specific regions to cover key markets, and then using agile teams to drive development and innovation.

In Mexico, sexual health brand Sico believed its core consumers to be young males; by analysing purchase data, the Audience Engine confirmed this group bought the products – but also revealed that the complete picture was more complex.  With content on the website including discussions on preventing sexual diseases and unwanted pregnancies, young females were also a vital element.  This illustrated to the brand that different messages were required to communicate effectively to both key audiences.

The second example is in the US, where media planning and buying is based on the Oracle Data Platform’s pre-determined purchase data segments, which look at the specific products or categories of products that people buy.  But trials showed that modelling raw data using the Audience Engine machine learning algorithms could increase ROI on media spend by 30%. Campaign effectiveness is improved, along with efficiency; accurate targeting makes it easier for Reckitt to reach more relevant consumers, cutting the cost of media by 20%.

Test and learn campaigns such as these inspired confidence by showing the Audience Engine to be highly credible; having quantified the benefits, Reckitt could then start to drive adoption so that it is used in as many campaigns as possible.

“The strategic mindset of Artefact’s multi-disciplinary teams has been instrumental in allowing us to leverage the different types of consumer data that we have, as well as build a sophisticated product that can scale globally and is now used every day by our teams around the world.”
Stanley Wang – Audience Engine Product Owner, Reckitt

FUTURE PLANS

Using the Audience Engine to continue to evolve as a digital and data led company

Reckitt’s objective is that the Audience Engine continues to deliver incremental value, making its business more effective and efficient; this will see it support both large and small brands across all its markets by enabling them to gain an in-depth understanding of who their customers are.  As technology develops, it will look for new ways to leverage data, adapting the Audience Engine to fit as the company becomes more digital and data led.

“The Audience Engine has changed how our business is able to operate and we will continue to evolve as it enables us to make better and more effective use of our data.”
Stanley Wang – Audience Engine Product Owner, Reckitt