Element Group · AI implementation
Element Group builds and runs AI systems for sales, marketing and operations. Each project starts with a business metric, such as revenue, cost or time, and a plan to measure the result.
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Marketing track record: brands we have run search and paid media for
Problem
Pilots stall. Data stays fragmented. Routine work takes as long as it did. These are the gaps we look for before proposing a build.
No clear owner, integration plan or success metric.
Sales, advertising and finance data sit in separate systems.
Call notes and reports are still written by hand.
No reliable before and after for cost, time or business outcomes.
AI projects
Three systems we built and still run inside our own group’s businesses: an ad audit finding, a cut in call write-up time and content output. Every figure is our own measurement.
Internal project · Consumer electronics · Three marketplaces
29%
Data lived in three marketplace accounts, accounting, the bank and spreadsheets. Leadership saw revenue but not which product was losing money. Now daily syncs feed unit economics per product, and a morning ad audit flags campaigns for review. Changes to live ad accounts wait for human approval.
Internal project · B2B sales
Call write-up time went from about 60 minutes to 5
Every call is transcribed and summarised straight into the deal history, with coaching notes for the manager and a team digest of objections: the reasons buyers give for saying no, and how often each comes up. Script changes now start from that digest.
Internal project · B2B services website
250
Topics come from live search demand. Agents draft, facts are checked against primary sources, and nothing is published until it passes a multi-layer quality gate. Experts review every draft.
If it can’t tell a revenue story, we don’t ship it.
What we build
Each system plugs into a workflow you already run, and we agree up front how its impact will be measured.
Sales
Sales calls turned into CRM notes, coaching points and a running count of the objections buyers raise.
Advertising
Campaign spend and sales data in one place. Campaigns are flagged for review before any budget changes.
Content
From topic research to reviewed drafts, with facts checked against primary sources before publication.
Leadership
Unit economics and channel performance in one view, with data updated automatically.
Customer service
Replies to reviews and questions drafted in your brand’s voice. A person approves each one before it is sent.
Team
Agents and playbooks your own people use in their own workflows. You get the method as well as the system.
We begin with an audit and a scoped pilot. The target for a first pilot is four weeks; the actual timing depends on the scope and the systems involved.
Choose one workflow, record the baseline, and agree the success metric and acceptance criteria.
Build the agreed workflow, test the integrations and review the result with your team.
Compare the result with the baseline, then decide whether to expand, revise or stop.
How we work
We start with an audit and a clear business case. If automation is a poor fit, we’ll say so.
A written scope with acceptance criteria. You sign off before development starts.
Code is reviewed at every phase. Work that touches financial actions, account access or personal data also gets a security review.
Each automation checks its result, not just that it ran. Empty output counts as a failure.
Actions with financial impact need explicit approval, and every one is logged.
In the systems we build, personal data is anonymised in-house before it reaches a third-party model.
A strategist, a marketer, an AI engineer and an analyst. Together they define the business case, build the workflow and check the numbers before and after.
Marketing track record
Before AI, our work was search, performance and product marketing, including for the brands below. It predates our AI practice and shapes which sales and marketing problems we choose to solve first.
| Brand | Sector | Work | Result |
|---|---|---|---|
| Polaroid | Cameras | Paid search and content | 4.2× revenue from paid search |
| Sony | Online store | Search, paid and display mix | 1.9× sales from paid traffic |
| Alibaba | E-commerce | SEO strategy and technical requirements for 1M+ pages | +386% organic traffic |
| Xiaomi | Consumer electronics | Search visibility for the US site, Google and Yahoo | +378% organic traffic |
| Yves Rocher | Beauty | Organic search | +193% organic traffic |
| GE Money Bank | Banking | Organic search | +345% site visits |
| Cisco | Web conferencing software | Search marketing programme on Baidu | +87% site traffic |
| Subaru | Automotive | New model launch campaign | 3.5× average CTR |
| Nespresso | Coffee | Organic search for the online store | 31% increase in queries ranking no. 1 |
| River Island | Fashion | SEO across 3,000 pages | 4,108 keywords ranking in the top 10 |
Selected marketing engagements completed before our AI practice. Results are drawn from our own case studies. All trademarks belong to their owners; no endorsement is implied.
Request the full case studyTeam · Local time
Where our teams are based, with the local time in each country.
Tell us which process you want to improve, which systems it uses and what you want to measure. We’ll tell you whether AI is a good fit and what a pilot could involve. If it isn’t, we’ll say so.
