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02 · Insights— The analysis

Customer personalization

Tailors offers, content, and experiences to each customer using their behavior and preferences.

Data updated

54
deployments
on record
12
industries
led by Tech & Comms
12
publish a quantified result
52 report any result
18 Jul 2026
newest deployment
publication date
§ 1

Where it is used

Tech & Comms accounts for 17% of these deployments.

  1. Tech & CommsRising · 2 in the last 6 months
    9
  2. RetailSurging · 3 in the last 6 months
    8
  3. ManufacturingEmerging · 0 in the last 6 months
    8
  4. FinanceBuilding · 1 in the last 6 months
    7
  5. AutomotiveQuiet · 0 in the last 6 months
    5
  6. Consumer & FoodQuiet · 0 in the last 6 months
    4
  7. Energy & UtilitiesQuiet · 0 in the last 6 months
    3
  8. Professional ServicesEmerging · 0 in the last 6 months
    2
8 of 12 industries
§ 2

What it delivers

12 deployments publish a number. The rest describe results in words, grouped below.

  1. Time & speed

    8 metrics

    Reduction · median and middle half
    −40%Median reduction −40%, middle half −25% to −83%, from 7 metrics
    Increase · median+60%1 metric · few

  2. Revenue & growth

    5 metrics

    No reductions reported
    Increase · median+35%5 metrics

  3. Customer experience

    3 metrics

    No reductions reported
    Increase · median+100%3 metrics · few

  4. Productivity & throughput

    1 metric

    No reductions reported
    Increase · median+60%1 metric · few

  5. Other quantified impact

    1 metric

    No reductions reported
    Increase · median+20%1 metric · few

Grey figures rest on fewer than 5 published metrics. Read them as examples, not as a typical result.

Results described in words

  1. Customer experience & trust80% of these deployments
    43
  2. New product / capability67% of these deployments
    36
  3. Speed & agility54% of these deployments
    29
  4. Scale & capacity30% of these deployments
    16
  5. Better decisions & insight17% of these deployments
    9
  6. Cost efficiency15% of these deployments
    8
6 of 8 result types
§ 3

How it is built

Microsoft is named in 44% of these deployments.

  • Custom-built84% · 37
  • Bought9% · 4
  • Mixed7% · 3

The build approach is known for 44 of 54 deployments (81%). The rest are left out.

Cloud providers named

  1. Microsoft24 deployments
    44%
  2. AWS19 deployments
    35%
  3. GCP12 deployments
    22%

Technologies that recur

  • Amazon Bedrock 16
  • Azure AI 8
  • Vertex AI 8
  • BigQuery 8
  • Azure OpenAI 6
  • Amazon SageMaker 5
  • AI 4
  • Amazon S3 4
§ 4

Deployments over time

14 deployments in the last six full months, against 7 in the six before. Counted by publication month since Oct 2023. 1 earlier deployments are not shown.

Compare momentum with other patterns
The lighter bar is Nov 2026, still in progress: 0 so far.
§ 5

Deployments of this pattern

All 54 in use cases
  1. 18 Jul 2026
    Retail

    Canadian Tire Case Study | Google Cloud

    Canadian Tire Corporation · GCP

    Canadian Tire Corporation, one of Canada’s largest retailers, used Google Cloud and Quantum Metric to gain a real-time view of loyalty-customer digital journeys across online and offline channels. The company built ingest jobs into BigQuery, captured roughly 600 signals per customer session, and used the data to run frequent personalization experiments and improve omnichannel shopping experiences. The program helped the retailer tailor offers and recommendations and support a loyalty program with more than 11 million active members.

  2. 15 Jul 2026
    Retail

    iFood: AI journey with AWS for personalization and fraud prevention

    iFood · AWS

    iFood, one of Brazil's largest delivery marketplaces, uses AWS generative AI to personalize the customer experience and support internal developer workflows. The company operates at very high scale, with more than 80 million orders per month across 330,000 partner establishments. iFood also applies AI-driven fraud prevention across the purchase flow, with users going through more than 100 AI models when buying through the app.

  3. 7 Jun 2026
    Finance

    Discovery Bank: Discovery AI hyper-personalization with Azure OpenAI in Foundry Models

    Discovery Bank · Microsoft

    Discovery Bank needed to scale hyper-personalized financial experiences and deliver faster, smarter client interactions without managing complex infrastructure. Using Azure OpenAI in Foundry Models and Azure Databricks, Discovery Bank built Discovery AI, a generative AI application that powers personalized recommendations for clients and helps service agents tailor their interactions with customers. Discovery AI doubled client engagement with Discovery Bank next best actions. The AI-powered experience reduced latency of response times by over 50% and improved client satisfaction through real-time, personalized financial insights.

  4. 7 Jun 2026
    Healthcare

    Moody Month uses Gemini 2.5 Pro and Vertex AI on Google Cloud to deliver privacy-preserving personalized women’s health insights

    Moody Month · GCP

    Moody Month built an AI-powered women’s health and wellness tracker on Google Cloud to deliver personalized hormone forecasts and research-backed advice. The company designed the platform to keep sensitive health data private by isolating user data in Firestore and avoiding exposure of raw user data to LLMs. It uses Cloud Run microservices, Gemini 2.5 Pro, Vertex AI, BigQuery, Looker Studio, and supporting Google Cloud services to generate, match, and visualize insights at scale.

  5. 3 Jun 2026
    Tech & Comms

    iZooto case study | Google Cloud

    iZooto · GCP

    iZooto uses Google Cloud to deliver 27B+ daily notifications, boosting engagement, retention, and monetization for global publishers. The platform supports an AI-powered recommendation engine for personalized content and uses Google Cloud services including Vertex AI, Document AI, BigQuery, Pub/Sub, Translation AI, Compute Engine, Google Kubernetes Engine, Cloud SQL, Cloud Storage, and Firebase.

  6. 27 May 2026
    Tech & Comms

    Chunghwa Telecom Builds Multiple Generative AI Solutions with Amazon Bedrock

    Chunghwa Telecom · AWS

    Chunghwa Telecom switched to Amazon Bedrock, accelerating the development of generative AI applications. These new applications include generating specifications documents for the software development lifecycle (SDLC), creating an interactive virtual English teacher, and developing a generative AI marketing assistant. Chunghwa Telecom is one of the largest integrated telecommunications providers in Taiwan. To improve artificial intelligence (AI) data security and governance, the company migrated its generative AI projects to AWS. With Amazon Bedrock, Chunghwa Telecom is saving developer hours and has also developed an immersive, interactive virtual English teacher for the first time.

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