Technology, data and AI. Chief Digital Officer
AI for the Digital Office
Your customers left at step four. Nobody knows why.
Digital teams have more data than ever and less time to act on it. Every fix waits in a release queue, every market needs its own content and customers now ask AI assistants before they visit. We map the Digital Office the way your team actually works, then put agents where they turn visits into revenue faster.
The short answer
It helps you grow conversion and digital revenue faster. Agents find where customers drop out of journeys, build and test fixes, personalise each visit, complete product content in every market and power search and shopping assistants.
Your team keeps the product vision, the brand and the experience design. The agents do the analysis, the variants and the content at scale, so changes that took weeks ship in days.
The mandate
Grow digital revenue and make every channel easy to use. Faster than competitors and the platforms can.
What the board measures you on
Digital revenue share
Of total revenue
Conversion
By journey and device
Active users
Web and app
Digital cost to serve
Tasks done online
Speed of change
Idea to live
Customer satisfaction
With digital channels
The canvas of the Digital Office
Most digital AI is a chatbot on the homepage. The bigger value sits in the journeys, the content and the speed at which the team can change both.
Canvas 1
What you run
Every digital place customers meet you.
Web, app and eCommerce
Sites, apps, stores and marketplaces.
Digital journeys
Search, browse, buy, service and account tasks.
Experimentation
Tests, releases and the backlog of changes.
Product content
Descriptions, attributes, images and translations.
Digital analytics
Funnels, sessions and the numbers you report.
Canvas 2
What you answer for
The things the CEO, customers and regulators hold you to.
Digital revenue and margin
Not just traffic.
Accessibility
Under the European Accessibility Act and your own standards.
Consent and privacy
How customer data feeds personalisation.
Readiness for AI shoppers
Whether AI assistants can read, compare and buy from you.
Where value leaks
Each one costs a fraction of a percent of conversion. Across every visit, every day, that adds up to real revenue.
01
Journeys that drop customers
Customers give up on a form, a filter or a checkout step.
Journey agents. Read session and funnel data, find where and why people leave and propose fixes.
Conversion
Drop off by step
02
A release queue for every change
Small fixes wait weeks for design and development.
Experience agents. Build variants inside your design system and set up tests for the team to approve.
Idea to live time
Tests per month
03
One experience for everyone
The same page for every visitor, whatever they came for.
Personalisation agents. Adapt content, offers and order to each visit, using consented data and context.
Conversion
Average order value
04
Search that can’t find
Customers type what they want and get nothing useful.
Shopping assistants. Understand plain language questions and guide customers to the right product or answer.
Search conversion
Zero result searches
05
Product content gaps
Missing attributes, weak descriptions and untranslated pages.
Content agents. Enrich, check and translate product content across markets, within brand and legal rules.
Listing completeness
Time to list
06
Invisible to AI shoppers
AI assistants can’t read your products, so they recommend someone else.
Agentic commerce agents. Structure product, price, stock and policy data so AI assistants can find and buy from you.
AI assistant referrals
Share of AI answers
Process lifecycles
We start from the platforms you already run. The orange steps are where an agent takes on the work, so your team spends its time on the experience, not the queue.
Visit to purchase
Every customer visit
Arrive
Search
Plain language
Agent
Browse
Personalised
Agent
Basket
Checkout
Drop off watched
Agent
Pay
Track
Typical systems. Salesforce Commerce Cloud, Shopify Plus, commercetools, Algolia
Experience change
Every fix and feature
Insight
From session data
Agent
Design
Build variant
Inside the design system
Agent
Test
Set up and read
Agent
Release
Measure
Typical systems. Optimizely, Contentsquare, GA4, Adobe Experience Manager
Product content
Every product, every market
Onboard
Enrich
Attributes and copy
Agent
Translate
Every market
Agent
Approve
Publish
Monitor
Gaps and errors
Agent
Typical systems. Akeneo, Salsify, Contentful, DAM
Digital self service
Every account task
Log in
Understand task
In plain language
Agent
Complete
End to end
Agent
Confirm
Hand over
With context if needed
Agent
Typical systems. Web and app platforms, CRM, service platforms
Agent intervention point
The Digital control tower
Not twelve analytics tabs. One live view of revenue, conversion and where customers drop off, with a brief on what to fix next.
Illustrative
Digital control tower
Sample data to show the view. Not client results.
Digital revenue
34%
▲ 3 pts of total
Conversion
2.8%
▲ 0.3 pts
Checkout drop
38%
At delivery, mobile
Idea to live
4 days
▼ from 21
Tests live
18
▲ 11
Listings complete
83%
3 markets behind
This week’s digital brief
Drop off
Delivery options page loses 38% of mobile checkouts
Date picker fails on two browsers. Fix and test ready
Search
14% of searches return nothing useful
Top terms mapped to products. Shopping assistant agent
Content
2,300 products missing attributes in German and Polish
Enriched drafts ready for approval
Winner
Simplified account sign up lifted completion by 19%
Rolled out to all markets
Drop off by checkout step, mobile
Basket
21%
Account
28%
Delivery
38%
Payment
12%
Delivery is the leak. Fixing it is worth an estimated €210k a month in revenue.
Illustrative example. Figures are invented to show how the view works. In discovery we build it on your own data and KPIs.
Your industry changes the agenda
The canvas stays the same. What customers do online, and why, does not. Here’s the question we hear most from digital leaders in each industry, and where agents help first.
CPG
How do we win on retailer sites and marketplaces we don’t control?
Product content and listing quality
FMCG
How do we keep thousands of listings right across many retailers?
Content enrichment and monitoring
Retail
How do we make online and store feel like one shop?
Personalisation and stock aware journeys
D2C
How do we lift conversion when traffic gets more expensive?
Checkout fixes and testing at speed
Automotive
How do we move car buying and service booking online?
Configurator and booking journeys
Healthcare
How do we make digital access easy for every patient?
Accessible self service journeys
Energy
How do we move switching, moving and billing questions online?
Self service and plain language help
Manufacturing
How do we sell spare parts and services online to dealers and buyers?
B2B search and parts content
Logistics
How do we let customers book, track and change shipments themselves?
Booking and tracking self service
BFSI
How do we cut drop off in applications without weakening checks?
Application journey analysis and fixes
B2B technology
How do we move buyers from trial to paid without a sales call?
Product led journeys and onboarding
Proof
Uplift in eCommerce sales from real time competitor pricing agents
Leading home appliances company
Of AI pricing suggestions accepted by the pricing team
Leading home appliances company
How the Digital Office connects
Marketing brings the traffic, sales and service depend on the journeys and engineering ships the changes. The agents that serve the Digital Office share the same platform and data as those offices, so a fix in one place shows up everywhere.
How we’d start
Pilot 1
Fix the journey that leaks most
↳
Journey agents find the top three drop off points in your busiest journey
↳
Fixes built as variants inside your design system
↳
Tested for a month against the current journey
Your decision
Which fixes to roll out, and which journeys to do next.
Pilot 2
Product content for one category
↳
Content agents enrich and translate every product in one category
↳
Checked against brand and legal rules, approved by your team
↳
Conversion compared with a category left as it is
Your decision
Whether to extend it across the catalogue and every market.
Both run under our Validation First Framework. They’re tested on your own data before you commit a larger budget, and if the numbers don’t hold, we tell you.
Your intervention map
Bring your funnel data, your release backlog and the journey you’re least proud of. We bring the Digital Office canvas. In one session we map it to your platforms and team, and mark where agents would pay back first.
01
Your Digital Office canvas
What you run and answer for, checked against how your product, design and engineering teams really work.
02
Your value chain
The canvas placed on your industry and customer journey, with the platforms behind every step.
03
Your intervention points
Each leak with an agent design, its controls and the KPI it moves. Delivered as a mind map, an architecture view or an interactive dashboard.
AI for the Digital Office, answered
What can AI do for the Digital Office?
Agentic AI helps digital teams grow conversion and digital revenue faster. Agents find where customers drop out of journeys, build and test fixes, personalise each visit, complete product content in every market and power search and shopping assistants. Changes that took weeks ship in days.
How can AI improve digital conversion?
Journey agents read session and funnel data to find exactly where and why customers drop out, then propose fixes. Experience agents build variants inside your design system and run tests, so the team decides from results rather than opinion. Most gains come from small fixes at the steps that leak most.
What is agentic commerce and why should we prepare?
Agentic commerce is when customers ask AI assistants to research, compare and even buy on their behalf. Those assistants read structured product data, prices, stock and policies. Brands with complete, structured data and an agent friendly checkout get recommended. Those without it become invisible.
Can AI personalise digital experiences without breaking privacy rules?
Yes, if it is designed in from the start. Personalisation agents work from consented first party data, respect each customer’s choices and log what they used and why. Much of the value comes from context, such as what someone is looking at now, rather than personal data.
Do we need to replace our commerce or content platform?
No. Agents work with Adobe, Salesforce Commerce Cloud, Shopify, commercetools, Contentful, Optimizely and your analytics. They speed up the work around the platform rather than replacing it.
Where should a Chief Digital Officer start with agentic AI?
With the journey that leaks most. Let agents find the top three drop off points, propose fixes and test them for a month. Product content enrichment on one category is a strong second pilot. Both show results in conversion within weeks.
