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Accenture Telecommunications Spain

Telefónica

Marketing Personalization

Telefónica needed to produce far more localized and personalized marketing assets across regions and dialects, but manual content production was too slow and expensive to support high-volume campaigns efficiently.

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135% savings in hours
249% increase in clickthrough rate
300 different content pieces
40 assets in several weeks

Reported impact

Business outcome

Telefónica increased content-production speed and scale, cut campaign cost and hours, improved clickthrough performance, and gained a reusable platform for hyper-personalized marketing across channels and regions.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement

Solution

Telefónica and Accenture built the Content Automation Tool, or CAT, as a multi-part platform for generating and optimizing marketing content at scale. CAT is integrated with Telefónica's marketing ecosystem and lets nontechnical users create brand-compliant assets from unified templates, while an automated dashboard supports reporting and management of micro-segmented campaigns. The platform applies generative AI and predictive heat-map capabilities to generate variations, estimate creative performance, and optimize messages using analytics from live campaigns. Its channel-agnostic design lets teams produce assets across multiple digital and physical formats through one interface, including outdoor digital screens and other media placements. By automating variant production and tying creation more closely to customer data and campaign performance, CAT shortens the cycle from concept to launch and gives Telefónica a reusable engine for hyper-personalized marketing.

Data flow

Marketing teams feed campaign templates and customer-segmentation needs into CAT, which uses generative AI and predictive heat-map capabilities to produce and optimize localized content variations. Performance data then flows into the automated dashboard so teams can refine messages, generate additional variants, and distribute assets across digital and physical channels through the same platform.

Solution architecture

4 components · 3 layers
  1. Compute
    • predictive heat map tools Estimate creative performance so Telefónica can optimize content before and during campaigns.
    • gen AI capabilities Generate and optimize content variations based on campaign data and performance analytics.
  2. Serving
    • Content Automation Tool (CAT) Provides the central interface where teams create brand-compliant, high-volume content variations without technical skills.
  3. Orchestration
    • automated dashboard Supports reporting and the efficient management of segmented campaign output.

Architecture clues

  • CAT is integrated into Telefónica's existing marketing ecosystem.
  • Performance analytics feed further automated content optimization.
  • Predictive heat-map tools are used before and during campaigns.
  • The platform is channel-agnostic and serves both digital and physical placements.

Evidence from the source

"CAT enabled the creation of over 300 different content pieces from a basic design template in just two days"
"CAT has also enabled a 96% rise in production efficiency and a 91% enhancement in time to market"
"During specific campaigns like 'Black Friday,' the clickthrough rate (CTR) increased by 249%"
"Leveraging sophisticated gen AI capabilities, it predicts creative performance using predictive heat map tools, generates and optimizes content variations based on real-time analytics."
"Telefónica ... has modernized its marketing strategies with the innovative Content Automation Tool (CAT)."
Transparency Evidence & methodology 100/100 reference value · 89% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    7 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Accenture

    Telefónica customer story

    First-party
    https://www.accenture.com/en/case-studies/song/telefonica-kisses-campaign
    Source type
    Vendor-published customer story
    Published
    Jan 7, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jan 7, 2026 · Accenture · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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