Reckitt
Reckitt uses generative AI to speed up marketing insights and ad localisation
Reckitt, the UK-based maker of Dettol, Lysol and Finish, used generative AI to turn consumer data into marketing ideas and to adapt ads for different countries. Its Chief Insights and Analytics Officer reports at least a 60% efficiency boost in marketing. The 60% figure comes from Reckitt through a Microsoft story; Reckitt's own June 2024 press release on its pilots reports the 30% and 90% figures.
Key figures
Copied exactly from the sources. Copy any figure with its citation.
at least a 60% efficiency boost
Efficiency gain in marketing, as stated by Reckitt's Chief Insights and Analytics Officer (the measure is not defined)1
approximately a 30% reduction
Reduction in the time needed to adapt and localise ads1
approximate 30% reduction
Reduction in the time to adapt and localise ads in the 2024 pilots, as reported in Reckitt's own press release2
up to 90%
Time saved on everyday marketing tasks such as post-campaign media analysis, with quality improving two-fold1
What it took
Cost, team size and timeline were not disclosed in the sources.
The problem
Reckitt sells household and health brands in many countries. Its marketers had to turn large amounts of consumer data into ideas, adapt each ad for different markets and analyse campaigns after they ran. Much of this work was manual and repetitive.
What they built
Reckitt worked with Microsoft on a Marketing Insights Generator. The tool looks for patterns in consumer behaviour and turns unstructured data, such as free text, into ideas for marketing. Reckitt also uses generative AI to adapt and localise ad assets for different countries and stages of the sales funnel. A separate trade report describes pilots on post-campaign media analysis and concept development.
How they did it
Reckitt put its data on Microsoft Azure and used Azure OpenAI together with Copilot for Power BI, which lets people ask questions of reports in plain language. It worked in multi-functional agile teams with a data governance team to keep data quality high. Marketers stay in the loop and decide what to do with the output. A 2024 trade report says the earlier pilots ran for four months and were led by Reckitt's IT and digital team with Boston Consulting Group.
Results
Reckitt's Chief Insights and Analytics Officer, Elaine Rodrigo, says the company has seen at least a 60% efficiency boost in marketing. Microsoft's story also reports approximately a 30% cut in the time needed to adapt and localise ads, and up to 90% less time on everyday tasks such as post-campaign media analysis. Reckitt's own June 2024 press release on its pilots gives matching figures for ad localisation and media analysis. Reckitt says ideas from the insights tool tested as well as, or in some cases better than, ideas from non-AI methods.
What to copy
Start with tasks that repeat in every campaign, keep a named person responsible for the final decision, and compare AI output with your current method before you scale.
All reported figures
| Measure | Figure | Citation |
|---|---|---|
| Efficiency gain in marketing, as stated by Reckitt's Chief Insights and Analytics Officer (the measure is not defined) | at least a 60% efficiency boost1 | |
| Reduction in the time needed to adapt and localise ads | approximately a 30% reduction1 | |
| Reduction in the time to adapt and localise ads in the 2024 pilots, as reported in Reckitt's own press release | approximate 30% reduction2 | |
| Time saved on everyday marketing tasks such as post-campaign media analysis, with quality improving two-fold | up to 90%1 | |
| Reduction in time spent on post-campaign media analysis, reported in Reckitt's own press release on its 2024 pilots | up to 90%2 |
Lessons for your project
Pick repetitive, high-volume marketing tasks first. Reckitt reports its biggest time savings on post-campaign analysis and ad adaptation across countries.
Keep people accountable for the final idea. Reckitt describes marketers as the human in the loop who judge what the tool suggests.
Test AI output against your current method. Reckitt reports that ideas from the insights tool tested at the same level as, or in some cases better than, ideas from non-AI insights.
Fix the data foundation before the AI layer. Reckitt consolidated its data on one cloud platform with a data governance team.
Caveats
- The 60% efficiency figure appears only in a Microsoft customer story (read through an archived copy), so the vendor presents it; it is Reckitt's own claim and no source explains how efficiency was measured. Reckitt's own press release of 21 June 2024 confirms the 30% and 90% figures, which it labels findings from four-month pilots, but it does not mention the 60% efficiency figure.
- The Microsoft page gives 6/26/2025 as its date but no start date for the tools. Reckitt's own dated report of pilot results is its press release of 21 June 2024, so the deployed date is given as the year only.
- Microsoft says concept development time fell by 60%, while Reckitt's own release says up to 60% in early findings. This case therefore does not use that figure as a metric.
- The two sources describe the tooling differently. Microsoft names Azure OpenAI and a Marketing Insights Generator. Reckitt's press release and the trade article describe four-month pilots led by Reckitt's IT team with Boston Consulting Group, using custom GPTs trained on Reckitt data. No model version is named.
- The sources do not state cost, team size or number of users.
Sources
- Reckitt uses Azure OpenAI to enhance marketing efficiency by 60%
Microsoft · 2025-06-26 · Vendor case study · microsoft.com
- Reckitt's first GenAI results demonstrate changing face of marketing during Cannes Lions International Festival of Creativity
Reckitt · 2024-06-21 · Press release · reckitt.com
- Reckitt Gen AI Pilots Optimizing Operations, Product Development, and Marketing
Consumer Goods Technology · 2024-06-21 · News · consumergoods.com
Summarized in our own words from the sources above. Spotted an error? See corrections.