Enterprise Account Executive · London

$11M+ in complex enterprise deals, in established markets and ones I built from zero.

A consistent enterprise closer across the UK, EMEA and emerging markets, with over $11 million in closed revenue and six and seven figure deals to C-suite buyers. I am as comfortable carrying an established patch as building one from zero, having been the first commercial hire at Twilio and Movable Ink. Equally at home with category-defining technology, CPaaS, AI products and AI governance, or competing in a mature, crowded market.

$11M+

Closed revenue

9+ yrs

Enterprise SaaS, CPaaS & AI

123%

Quota at OneTrust

Top 10/250

EMEA at Twilio, twice

Quota attainment

Consistent overachievement across three companies.

Full fiscal years shown against target. Hover any bar for the actual versus quota.

100% target

300%

$600k vs $200k

Twilio Y1

169%

$1.35M vs $800k

Twilio Y2

173%

$2.6M vs $1.5M

Twilio Y3

123%

£800k vs £650k

OneTrust

105%

£290k vs £275k

SFDC Y1

129%

£450k vs £350k

SFDC Y2

Figures in local currency: USD at Twilio, GBP at OneTrust and Salesforce. Twilio year four was a partial year (exited Q3).

Selected work

Three deals, from how I found them to what they delivered.

Each one walks the origination, the sell, the real challenges and the outcome. Customer commercials are kept off the page; the detail lives in conversation.

Flagship deal · complex enterprise

One of Africa's largest banks

$1.2M ACV · $4.3M TCV

18-month cycle · SMS & WhatsApp

How I found it

An anchor target in a territory I was hired to build from zero. I tiered the market first, then ran deep, BASHO-style research on the top accounts: company reports, financials, executive interviews and talks, mapping the group, its subsidiaries and the real decision makers and influencers before I made contact. The bank was already a small customer on a fraction of its potential, so I opened a fresh conversation through their innovation centre rather than the existing buyer.

How I sold in

Trust-first discovery, with MEDDPICC and Challenger underneath. I worked from the group's stated initiatives down into the departmental challenges blocking them, then quantified the cost of the status quo. The wedge was a self-service WhatsApp chatbot through the innovation centre; from there I ran a land-and-expand into a multi-country agreement and a large SMS deployment in the home market. I orchestrated a deep cast: solutions engineering, architects for the data flow, deal desk and legal, a local partner for cross-border data, the Meta team, and a US-based financial-services product expert, capped by a two-day on-site hackathon. I also resolved a structural pricing gap in the home market that had cost earlier deals, working with the network side to renegotiate local carrier inventory and designing a registration-based local pricing model that unlocked it.

Quantitative challenges

Communications spend fragmented across five African markets and multiple local vendors, with unpredictable cost.
Roughly 8% of total comms cost was avoidable through centralisation, the figure that anchored the business case.
An 18-month cycle into a large, multi-function buying committee.

Qualitative challenges

A siloed, inconsistent comms approach across the group and its subsidiaries.
A conservative fraud and compliance posture, making the bank cautious about a new customer channel.
Cross-border data-transfer rules across the markets in scope.
Getting a regulated bank comfortable putting sensitive traffic onto WhatsApp.

Outcome

$1.2M ACV and $4.3M TCV across SMS and WhatsApp, with a multi-country footprint. The commercial structure I designed became a repeatable model that opened local pricing for the wider market, and the bank moved from fragmented vendors to a centralised, self-service communications layer.

What it shows

A long, multi-stakeholder enterprise cycle run end to end, with the discovery to build the business case and the commercial creativity to turn one account into a vertical.

Martech transformation

A leading African streaming and pay-TV business

~$200k · churn down 25%

CDP · multichannel retention

How I found it

An existing CDP customer. Rather than wait for a renewal, I went back into the account to ask where else their customer data could create value, and landed on retention for their premium streaming brand.

How I sold in

I brought the Head of Digital, the Head of IT and the CDP owner into one conversation to map where the data sat and how it could be activated. We co-designed a data-led, multichannel programme across in-app, SMS, WhatsApp and email, built around viewing history and show feedback, aimed at continuous login, advocacy and reactivation rather than blanket sends.

Quantitative challenges

Subscribers logging in roughly once a week.
Churn around 15% among customers who bought and did not renew.
Marketing and outdoor spend rising with no measurement of impact.

Qualitative challenges

Blanket communications across every new show, with no segmentation.
Marketing, IT and the CDP function working in silos.
Openness to using data, but no internal view of how.

Outcome

Around $200k across WhatsApp, email and Braze. Churn fell 25% in the first year, feedback on local shows improved, and the programme was written into their forward strategy as part of the premium tier.

What it shows

The closest analogue to modern AI and martech selling: turning a CDP and first-party data into a measurable retention motion, across siloed stakeholders.

AI governance

A global investment-management firm

~£250k · 6-month cycle

Privacy → data discovery → AI governance

How I found it

A regulated, enterprise financial buyer at the start of a wider data and AI transformation. The entry point was privacy, but the more strategic value sat further along the journey, in data discovery and, ultimately, AI governance.

How I sold in

I compressed the first deal on a clear privacy wedge, then orchestrated the expansion into data discovery and AI governance, growing the mandate as the buyer's confidence and internal sponsorship grew.

Quantitative challenges

A six-month cycle compressing what is often a multi-year adoption arc.
A three-stage expansion inside a single account.

Qualitative challenges

AI governance was a category most buyers were only beginning to understand.
A regulated buyer with a high bar for risk.
Building internal sponsorship to justify each expansion.

Outcome

Around £250k across six months, structured as a land-and-expand from privacy into AI governance, one of three first-to-market AI governance projects I ran in financial services.

What it shows

Selling category-defining, regulated technology and growing a single wedge into a multi-stage transformation. Directly relevant to AI-native go-to-market.

Track record at a glance

More of the patch, in numbers.

Account	What	Value
A major African airline	Comms, OTP and a contact-centre consolidation (six systems into one)	$1M / 2yr
Amref	Automated recorded calls and SMS for region-specific training	$550k
SpatialChat	Video, plus further customer-engagement comms	$500k+
Paystack	Contact-centre and comms channels	$400k / 2yr
Pep	Contact centre and WhatsApp	$150k
AB InBev	Voice	$150k
A European iGaming operator	Comms and security	$150k
MTN	Converted to channel partner for OTP, deployed into wealth-management customers	$100k initial

Plus the case-study deals above. Headline career total: $11M+ closed.

How I build pipeline

I tier a region before I touch an account.

I start by deciding where to play, not which logo to chase. At Twilio that meant a four-tier country model, scored on what we could realistically sell into each market: technology access, deliverability and pricing position, the largest industries and their TAM, and the economic and political factors that change the game, like currency constraints or a lack of open competition. I run the same lens on verticals and accounts, mapping them on two axes: where the demand and buying intent actually sit, and where we have the proof, the case studies and references, to win. The priority is the overlap, where real demand meets real evidence.

From there I score and rank a target list on a weighted basis, demand signals, fit, evidence and reachability, rather than gut feel, then tier the accounts: top 20, top 50, top 150, then the rest of the market. For the top accounts the aim is to know everything, including becoming a customer myself to learn what works and what does not. More recently I have built in a newer signal: how buyers surface in AI search and answer engines, and where a category is structurally exposed to zero-click answers, which increasingly shapes both who I target and the angle I lead with.

A high-volume outbound machine. An SDR and Apollo, 800 to 1,000 new contacts and up to 4,000 emails a month.
A BASHO motion. Two accounts a week, roughly 15 contacts each, deep research on contact and account, four emails over two weeks, around 40% response.
Channel partners. Two official and six unofficial, trained and managed, engaged in the mid-to-late deal.
Marketing and local brand. Internal ad spend to build awareness, plus webinars and event speaking.
Vendor and past-customer mining. Existing relationships with Salesforce, Microsoft and HubSpot, plus former customers.

The split that mattered

Motions 1 and 2 drove roughly 60% of revenue, partners around 15%, and vendor and past-customer mining around 10%.

Discovery: trust first, framework underneath.

MEDDPICC, Challenger and BANT sit under the conversation, not on top of it. The first meeting is not a pitch, it is establishing whether we are a fit and positioning myself as a trusted advisor who understands the buyer's market and competitors. From there I work goals, then the initiatives behind them, then the departmental challenges blocking them, then the real cost of those challenges across OPEX, CapEx and customer and employee attrition. Then I introduce the challenges they have not named yet, regulatory exposure, or what a close competitor is already doing, and reframe everything against the cost of inaction.

AI, in practice

AI is woven through how I sell, not bolted on.

I use it daily across the sales and marketing process, and I build with it outside work too.

Research and targeting

Deep account and contact research, building dossiers and qualifying target lists far faster than by hand, then mapping demand against evidence to decide where to focus.

Competitive intelligence

Building and maintaining competitive positioning, for example a playbook on AI positioning across email, SMS and WhatsApp, so I can hold my own against any competitor on a call.

Outbound and personalisation

Drafting and tailoring outbound at the contact level, anchored on a buyer's own stated priorities rather than generic templates.

Collateral and enablement

Producing demo decks, GTM documents and account plans, and turning messy data into something usable, like consolidating thousands of CRM records into a clean vertical view.

Workflow automation

A daily AI briefing on the industry, plus lighter automations such as inbox summarisation, to stay on top of a large patch.

Demand and AI-search analysis

Auditing how buyers surface in AI search and answer engines, and where a category is exposed, as a newer input to targeting and messaging.

Beyond work

Outside work I build and experiment constantly. I am building a music app on Lovable, make music with Suno, and play with AI video creation. It keeps me close to where these tools are heading, which is exactly the kind of technology I want to sell.

Skills

What I bring to the patch.

Sales motions

New business developmentGreenfield territory creationLand and expandOutbound prospectingPipeline management and forecastingPartner and channel development

Methodologies

MEDDPICCChallengerSandlerBANTNegotiation

Markets and domains

UK, EMEA and emerging marketsSaaS, CPaaS and AIAI product salesAI governanceEnterprise and C-suite

Building teams

Hiring and ramping SDR and AEEnablementFirst commercial hireFounder

About

Travis Andrew is a London-based enterprise account executive with around a decade across Twilio, Salesforce, OneTrust, Movable Ink and Mailchimp, plus a company he co-founded, built and sold.

The throughline is building. He is happiest opening a market that does not exist yet, and he has done it from zero more than once. He sells with MEDDPICC, Challenger and a trust-first discovery style, and he is drawn to category-defining technology, most recently AI products and AI governance.

Get in touch

Open to enterprise AE and founding sales roles at AI-native and growth-stage companies.

Connect on LinkedIn Email me