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Proof B Live confirmed

Microsoft

conversational web agent for acquisition and activation on a company's own product pages

IndustryTech & SaaSLeverAcquisitionFamilyConversationImplementationMartech platformStageconsideration
Pattern proven in 5 industries still untouched in Banking, insurance & fintech, Luxury & beauty, Media & entertainment +7 See the pattern map
10 fois plus eleve
Likelihood of moving to signup after interacting with the agent
"ten times more likely to move forward with signing up for services" S1

The Ask Microsoft web agent, built with Copilot Studio, makes Microsoft.com visitors ten times more likely to sign up, increases Azure product trials by 16%, and reduces human escalations by 70%.

Key points

  • Ask Microsoft conversational web agent for acquisition on Microsoft.com.
  • Built with Copilot Studio, generative orchestration and RAG over product content.
  • Visitors 10 times more likely to sign up, +16% trials on Azure, -70% human escalations.
  • Evidence B, confirmed status.

Objective

Turn navigation help on Microsoft.com into an acquisition lever. The Ask Microsoft agent answers visitors, steers them to the right offer, and raises the likelihood that they sign up or start a product trial, while reducing reliance on human chat.

The deployment

Microsoft built Ask Microsoft, a conversational web agent, with its own Copilot Studio, to help millions of visitors find information on Microsoft.com. The agent moved from rigid topic flows to a generative orchestration that understands intent and holds multi-turn conversations. A first agent was deployed in a few weeks, then extended to ten additional product sites at a pace of two per week. On the Azure pages it drives more trials; across the board, visitors who use it view more pages and sign up far more often.

Results Proof B

10 fois plus eleve
Likelihood of moving to signup after interacting with the agent
"ten times more likely to move forward with signing up for services" S1
16% de plus
Product trial initiations on the Azure site
"16% more initiations of product trial" S1
jusqu'a 70% en moins
Reduction in escalations to a human
"up to 70% fewer human escalations" S1
jusqu'a 61% inferieure
Response latency of the updated agent
"up to 61% lower latency" S1

Official, quantified Microsoft case study on its own deployment (Ask Microsoft), with conversion and engagement metrics. A single substantial source (Microsoft customer story), corroborated by the same vendor's Copilot Studio documentation, hence a B rather than an A.

How it works

Documented architecture
reponse multi-toursorientation vers inscription ou essai Visiteur de Microsoft.com Pages produit Microsoftet Azure Agent web Ask Microsoft Microsoft Copilot Studio Contenu et documentationproduit Inscription ou essaiproduit

The stack in detail

  • plateforme Microsoft Copilot Studio Low-code platform used to build the Ask Microsoft agent, moved from rigid topic flows to multi-turn generative orchestration.
  • llm Modeles generatifs de Copilot Studio LLMs built into the platform for intent understanding and response drafting; the exact model is not named in the customer story.
  • outil RAG sur le contenu produit Microsoft.com Retrieval-augmented generation: the agent answers from indexed product documentation and steers to the right offer.
  • infra Microsoft Azure Cloud foundation of the setup; the Azure product pages are also the scope of the 16% trials gain.

How it runs, concretely

For ops teams
CadenceReal-time on each session on Microsoft.com, with rapid iterations of testing and tuning the agent
Operated byMicrosoft's web and digital marketing team, on Copilot Studio
  1. 1
    Intent understanding AI

    The generative orchestration interprets the visitor's natural-language request across multiple turns.

  2. 2
    Answer and steering AI

    The agent answers from product content and guides toward the right offer or SKU.

  3. 3
    Prompt to trial or signup AI

    On product pages, it pushes toward starting a trial or signing up for the service.

  4. 4
    Extension to other sites Marketing / web team

    The team replicates the agent on new product sites at a pace of two per week.

  5. 5
    Conversion measurement Marketing / web team

    Move to signup, trials started, and pages per session are tracked to steer the agent.

The signal that drives it

The intent expressed by the visitor and the indexed product content. Without up-to-date product content to query, the agent steers poorly and the conversion gain is lost.

How your customers perceive this type of use

Sourced studies

Les consommateurs n'acceptent pas les chatbots par defaut : 64% prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (Gartner, 2024) et pres d'un utilisateur sur cinq du service client par IA n'en retire aucun benefice (Qualtrics, 2025). L'acceptation se construit sur trois conditions mesurees par Salesforce : savoir qu'on parle a une IA, pouvoir escalader vers un humain, comprendre la logique de l'agent.

64%
Consommateurs qui prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (2024)
53%
Consommateurs qui envisageraient de passer a un concurrent s'ils apprenaient que l'entreprise prevoit d'utiliser l'IA pour le service client (2024)
pres de 75%
Consommateurs qui veulent savoir s'ils communiquent avec un agent IA (2024)

Acceptance conditions

  • Etre informe qu'on parle a une IA et non a un humain (pres de 75% le demandent, Salesforce 2024)
  • Un chemin d'escalade clair vers un agent humain (45% plus enclins a utiliser l'agent IA, Salesforce 2024)
  • Une logique de l'agent clairement expliquee (44% plus enclins, Salesforce 2024)

Red lines

  • Rendre l'humain injoignable : c'est la premiere inquietude des consommateurs sur l'IA dans le service client (Gartner 2024) et 50% craignent que l'IA les coupe du contact humain (Qualtrics 2025)
  • Remplacer le service client par l'IA sans alternative : 53% envisageraient de partir chez un concurrent (Gartner 2024)

Sources: Salesforce 2024 · Gartner 2024 · Qualtrics 2025

See full acceptance: by country, by use, by generation

How to replicate

Inference, not sourced

Data prerequisites

  • indexable product content and documentation
  • clear offer and SKU taxonomy
  • analytics instrumentation on conversion

Org prerequisites

  • a web/marketing team able to iterate on the agent
  • governance of scope and tone

Possible stack

  • low-code agent platform (Copilot Studio or equivalent)
  • RAG engine over product content
  • conversion analytics tool
Team to operate1 web project lead + 1 low-code builder + 1 product content owner, with analytics support.

The plan, step by step

  1. Step 1
    Scope a single product line, gather the corresponding content, and set a measurable conversion objective.Deliverable: Validated scope, product content corpus, and baseline KPI.
  2. Step 2
    Build the agent in the low-code platform, enable generative orchestration, and connect the product content.Deliverable: Working agent in pre-production.
  3. Step 3
    Test response accuracy, tone, and human escalation internally, and instrument conversion analytics.Deliverable: Validated agent with signup/trial tracking in place.
  4. Step 4
    Go live on a first site and compare signups and trials of visitors exposed to the agent.Deliverable: First conversion readout versus unexposed visitors.
  5. Step 5
    Replicate the agent on the other product sites at a steady pace, with the same measurement framework.Deliverable: Agents deployed in series and consolidated conversion reporting.

First step: Scope an agent on a single product line with the corresponding content and a measurable conversion objective.

Sources

  1. S1 Microsoft uses Copilot Studio to reshape customer experience and drive higher engagement Interested party microsoft.com · 2026-02-27 · accessed 2026-07-11 archive pending
  2. S2 Microsoft Copilot Studio | Create AI Agents Interested party microsoft.com · accessed 2026-07-11 archive pending