ABM & Lead Generation Manager (Bangkok-based, relocation provided)

A

bout Agoda

At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.

Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.

No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.

About the opportunity Within Booking Holdings, an enhanced and more connected B2B business is being built within Booking Holdings consolidating the businesses of Booking.com, Priceline and Agoda into a single global division (“New B2B Business”) About the role
A build role that owns the entire acquisition funnel for the named universe - from top-of-funnel demand generation to the deepest 1:1 account plays - weighted toward ABM depth. You run one tiered account-based motion: 1:1 & 1:few (ABM) where the value is, and a capped 1:many (Lead Gen) engine over the tail of the same named list. The art of the role is allocating finite team capacity across tiers - protecting 1:1 depth (the deep committee deals fund the whole program) while running an efficient 1:many engine. Player-coach: with a two-person team you personally carry the top 3–5 marquee accounts. Expect roughly 60% leadership / 40% own book; the discipline is protecting the leadership half when your own accounts heat up.

What you will do

• Own the target universe and the full funnel: tier the named list with BD; decide 1:1, 1:few, or 1:many treatment; set goals, capacity allocation across tiers (:70% toward ABM), and operating rhythm.
• Run a capped 1:many Lead Gen engine over the tail - templated, archetype-segmented campaigns built with the shared Marketing Ops Specialist, routed cleanly to BD - deliberately bounded so it cannot crowd out the deep work.
• Carry the marquee accounts yourself (player-coach); co-own named accounts with BD; guide committee mapping; own the multi-product narrative and land-and-expand path.
• Direct bespoke content and exec engagement; build the playbook; define and own account-level and funnel measurement with MarOps/RevOps; lead and grow the team; sell the program internally.

What you will need (required)

• 6+ years in B2B marketing and/or sales, with 3+ years in ABM or named-account field marketing.
• Full-funnel range - you can run both deep 1:1 ABM and scaled 1:many demand generation against a named list, with the judgment to allocate finite capacity (purely high-volume demand gen with no account depth is not the profile).
• Player-coach appetite; demonstrated BD partnership; buying-committee fluency; multi-product selling; account + funnel measurement literacy; CRM/MAP fluency; people leadership; comfort building from scratch.

Nice to have

• Travel/fintech/loyalty/marketplace or partnership-led experience; ABM-platform exposure; self-serve funnels; ITSMA/ABM certification; new-function or post-merger experience.

Why 70/30 (best-practice rationale)
At the leadership level, 70/30 keeps the function’s identity anchored in depth: the committee deals carry the revenue and are the fragile, hard-to-rebuild capability, while the scaled engine is a controlled feeder rather than a competing P&L. Capping Lead Gen at :30% of team capacity lets one Marketing Ops Specialist and a bounded automation motion serve the tail without pulling strategists off marquee accounts. Recommended default when the strategic named list is the primary prize.

How we will measure success
Primary (70%): committee engagement depth, joint account plans adopted, exec milestones, pipeline influenced, multi-product expansion, and deal velocity on strategic accounts. Secondary (30%): qualified pipeline and meetings from the capped 1:many tier, funnel conversion, and graduation of warming tail accounts. Plus team growth and playbook quality. #STRA#ANLS#MRKT#3 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #washdc #tirana #yerevan #sydney #melbourne #perth #vienna #graz #baku #minsk #brussels #antwerp #ghent #charleroi #saopaolo #sofia #toronto #vancouver #montreal #shanghai #beijing #shenzhen #zagreb #cyprus #prague #Brno #Ostrava #copenhagen #cairo #alexandria #giza #estonia #helsinki #paris #nice #marseille #rouen #lyon #toulouse #tbilisi #berlin #munich #hamburg #stuttgart #cologne #frankfurt #dusseldorf #dortmund #essen #Bremen #leipzig #dresden #hanover #nuremberg #athens #hongkong #budapest #bangalore #newdelhi #jakarta #bali #bandung #dublin #telaviv #milan #rome #naples #turin #palermo #venice #bologna #florence #tokyo #osaka #yokohama #nagoya #okinawa #fukuoka #sapporo #amman #irbid #riga #beirut #tripoli #vilnius #luxembourg #kualalumpur #malta #chisinau #amsterdam #oslo #jerusalem #manila #warsaw #krakow #sintra #porto #braga #cascais #loures #amadora #almada #doha #alrayyan #bucharest #moscow #saintpetersburg #riyadh #jeddah #mecca #medina #belgrade #singapore #bratislava #capetown #johannesburg #seoul #barcelona #madrid #valencia #seville #bilbao #malaga #oviedo #alicante #laspalmas #zaragozbanga #stockholm #zurich #geneva #basel #taipei #tainan #taichung #kaohsiung #Phuket #bangkok #istanbul #ankara #izmir #dubai #abudhabi #sharjah #london #manchester #edinburgh #kiev #hcmc #hanoi #sanaa #taiz #aden #gibraltar #marrakech #lodz #wroclaw #poznan #Gdansk #szczecin #bydgoszcz #lublin #katowice #rio #salvador #fortaleza #brasilia #belo #belem #manaus #curitiba #portoalegre #saoluis data representation data analysis SQL data analytics analytics python (programming language) data mining data science r (programming language) tableau analytical skills data visualization databases business analysis business intelligence (bi) microsoft sql server machine learning statistics microsoft power bi java finance shopee traveloka google facebook ctrip trip.com makemytrip grab amazon pandas (software) artificial intelligence (ai) information technology capital one accenture upwork deloitte mckinsey bain microsoft uber lyft gojek lazada alibaba shopify expedia skyscanner

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