The Power of Personalization: Ocado Retail’s Strategy to Boost Revenue and Lower Churn
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Retailers are becoming more skilled at making individual customers feel heard and valued. This is a necessity given the fact that 66% of respondents to a McKinsey survey stated that they expect email marketing messages to be tailored to their needs. While marketing personalization expertise is growing, it’s still difficult to manage, especially at scale.
Ocado Retail, one of the world’s largest dedicated online grocery retailers, delivering to over 645,000 customers in the U.K., has made personalization integral to its success.
Let’s look at how Ocado retail worked with Google Cloud and partner Cognizant to develop a new data platform to power its personalization efforts from the ground up.
Unifying data for more holistic, powerful personalization
To achieve its goals of personalization at scale, Ocado Retail needed a central data warehouse that could turn all forms of merchandising, advertising, business, and customer intelligence data into actionable insights. It wanted a means to accelerate customer segment identification, as well as the ideation and launch of relevant campaigns.
“We standardized on Google Cloud, including BigQuery, as the foundation for our data platform because we knew it was the right solution for now and the future,” says Kieren Johnson, Head of IT at Ocado Retail. “We have an incredibly lean team and we needed a partner with exceptional expertise to help build an ambitious enterprise data warehouse to provide powerful insights. Cognizant was also the clear choice to help us get there.”
Cognizant worked closely with Ocado Retail to make sure its expertise in Google Cloud and other technologies aligned with Ocado Retail’s vision to drive more advanced personalization at higher scales using machine learning. The partner helped build the foundation on BigQuery, and then incorporated other Google Cloud tools such as Cloud Run, Vertex AI, and Vertex AI Natural Language to provide no-ops, all-code warehousing, and analytics capabilities.
Cognizant also took advantage of the Google Cloud Partner Success Services (PSS) program to ensure best practices were being followed throughout the project. PSS provided advisory services that guided Cognizant through the highly complex process of building the new data warehouse for Ocado Retail on Google Cloud.
Building the enterprise data platform in this way allows Ocado Retail to leverage the full power of cloud-based analytics while maintaining a lean team. It also allows the company to greatly scale up its personalization efforts.
Making customers feel valued at every touch
The work Ocado Retail has done with Google Cloud and Cognizant has positioned it to make its growing customer base feel valued, understood, and supported in every interaction. Before launching the project with Cognizant and Google Cloud, Ocado Retail was only able to run a couple of campaigns per week and knew it lacked optimal insight into each campaign’s efficacy.
“We now run 10 times the number of campaigns we used to with the help of the data platform Cognizant built on Google Cloud,” says Kieren. “We run multiple campaigns every day for different customer segments, and all of that increased activity is entirely driven by data insights. The positive impacts on our marketing and customer service performance have been clear. We’re now working to expand what we do.”
Ocado Retail has enjoyed solid growth since the new data platform went live, including a 13% rise in active customers during fiscal year 2022, and has also seen a reduction in churn. It attributed these improvements to being better able to tailor products and communications to specific customer preferences.
Throughout the project, Cognizant supported data clean up while maximizing the scalable, flexible, and future-proofed data analytics infrastructure offered by Google Cloud.
Increasing data-driven actions
Ocado Retail plans to provide more data-driven insights to its commercial suppliers through a product called Beet Insights. So far, Beet Insights offers suppliers with intelligence about how their products are performing on the shelves. The result has been improving the role data plays throughout the supply chain, from production to purchase and beyond.
“By putting real-time insights about costs, marketing spend, and supply-funded activities into the hands of our commercial team and buyers, we are better positioned to improve our profits,” says Kieren. “At the same time, building data analytics into every part of our business will allow us to build on our personalization efforts.”
From the project’s inception, Ocado Retail ensured that the platform would be scalable and dynamic. Now, it is working to feed more data sources and streams into the warehouse to accelerate time to insights. Ocado Retail believes this next step in the evolution of the platform will unlock even more opportunities to initiate high-impact programs that transform personalization and every customer interaction.
Learn more about what Google Cloud and partners like Cognizant can do for your customer intelligence and personalization.
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Google’s AutoML Vision Helps AES Fight Climate Change
Global warming is one of the big challenges of our times; if not the biggest challenge of our times, says Andres Gluski, President and CEO, AES, a Fortune 500 company that generates and distributes renewable energy in 15 countries to help end climate change.
AES relies on Google’s AutoML Vision to assess damage to its hundreds of wind turbines. It uses drones to inspect and photograph its turbines, but these drones typically take 30,000 images, and each one must be examined–which can be extremely time-taking.
With Google Cloud’s AutoML Vision, AES can use machine learning to auto-detect damage so that engineers can spend less time identifying damage and more time repairing it.
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Engage and Translate: Text and Audio Chat in 100+ Languages
As users worldwide connect to the internet and work remotely, it’s more important than ever to make interactive applications chat in many languages.
But when users speak 100s of languages, this quickly can get challenging. Where to start? If you are new to translation, Sarah Weldon, the Product Manager for Cloud Translation, and Dale Markowitz, an Applied AI Engineer and Developer Advocate touch on a couple of simple starters, then provide examples of how you could advance your translations once you have gone further along the learning curve.
They also share how the Translation API can quickly globalize an app, with no multilingual expertise required. Increasing language coverage can drastically increase engagement, even for internal applications. For example, when Mercy Corps integrated Translation API in their internal hub, traffic volume increased 70%. Learn about integrating the Google Cloud Translation API Advanced with a chatbot client, using the machine translation glossary feature to control a set of terms for more relevant translation.
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Since 1994, IDOM, Japan’s leading buyer and retailer of used cars, has enjoyed success in the auto industry with a simple yet traditional business model: buy pre-owned vehicles directly from car owners and auction them to third-party dealers, or sell them to other consumers at retail stores.
In an increasingly frugal economy, Japanese consumers are buying fewer new cars. Most young urban workers take public transport, a cheap alternative for getting from point A to point B. Additionally, people who do own cars are keeping them longer: the average period of ownership is 7.5 to 10 years.
Although Japanese consumers are buying fewer new cars, used car sales are steadily on the uptick. Pre-owned car sales in Japan rose by 1.7% in 2015—the first big spike in three years. IDOM dominates this industry with about 40% market share, and it wanted to continue to take advantage of this growing market trend.
To do so, IDOM reinvented its marketing strategy, using Google’s machine-learning technology to make full use of its available customer data. The brand’s main goal was to attract more prospective car sellers to its physical stores because (1) that’s where they could close trade-in deals and (2) sourcing used cars efficiently is integral to the success of its business model.
Secondly, rather than measure marketing success solely on clicks, views, brand awareness, or favorability, IDOM relied on data to determine which advertising techniques—including phone calls and customized ads to prospective sellers—turned a real profit.
After successfully identifying and targeting existing car owners with a high chance of selling their car, it was only natural for IDOM to leverage this approach to identify and target potential customers with a higher chance of buying a car—key for the other side of its business as well. Thus, IDOM also showed customized ads to potential car buyers and prioritized follow-up phone calls to high-value potential car buyers.
Find out how IDOM increased the number of sellers and buyers visiting its stores by a whopping 25% and grew gross profits by 300% in a key market segment. Download now!
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Breakthrough Insights Across the Life Sciences Value Chain
New science and patient centricity require increasing reliance on data and deeper insights.
Accenture’s life sciences customers have been demanding answers to this need, and want a solution with an open platform.
Enter INTIENT, Accenture’s life sciences platform that is powered by Google Cloud.
INTIENT generates insights throughout the life sciences value chain from early research through pivotal clinical trials all the way through to delivering care to patients.
In this video, Kevin Julian, Senior Managing Director, Life Sciences, Accenture and Michael Stapleton, Senior Industry Executive, Accenture, discuss enables ground-breaking possibilities through applied intelligence, including the development of personalized therapeutics tailored to a patient’s genetic makeup, the utilization of real world data/evidence in clinical trials, better identification of patients for trials, development of digital therapeutics, and improved patient outcomes — in other words, better regimen adherence.
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Satellites Can Help Map Carbon Emissions By Looking at Images of Power Plants!
Did you know that Satellites can now help track power plants and determine if they are on or off? And did also know that compute processing that classifies over 59 trillion bytes of data from over 11,000 sensors from 300 satellites is done on on Google Cloud?
Google Cloud’s sustainability initiatives along with its cutting-edge, powerful technology and products are leveraged worldwide by organizations, non-profits and governments to keep a check on greenhouse gas emissions and build self-reporting, power monitoring platforms. Climate TRACE, a collaborative data sharing project with 50+ organizations is dedicated towards this cause by building a visual and meaningful way on a web app. In this video you can learn how generate geo-spatial model that can view the images of power plants gathered from satellite called Sentinel-2 to assess emissions from power plants. Watch the video to learn Google Cloud’s vehement role in funding and staffing special initiatives with Googlers who are experts in AI/ML, UX, data analytics and more!
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