B2B Go-To-Market Playbook for Logistics Tech: Find the Buyer, Land One City, Expand on Proof

I was VP Global Performance Marketing at Locus from February to October 2022, and we built $4.2M of pipeline in H1 CY22. Locus was acquired by IKEA (Ingka Group) in October 2025. What follows is my working view of how this category buys, not a Locus result.

The first contract is the easy part: a head of last-mile operations pilots one city to fix a problem they own. The rest of the network is a second sale, with the COO, often the CFO, IT and city managers attached to their spreadsheets. Run it as a routine upsell, and a competitor who pitches a full transport management suite to the COO can win it.

Timing is the other trap. GTM Alpha's sector note for logistics tech describes the usual motion as "Enterprise sales with a pilot at one hub or city, often timed around peak-season planning." Volumes peak around festivals and sale events, and many teams avoid system changes then. Ask each account when its peak and freeze fall, and plan back from that.

Buyer types differ too: a 3PL sells delivery and is held to its clients' SLAs, a retailer treats delivery as a cost and a promise, and a manufacturer often contracts distribution out to a 3PL. So the example starts with one buyer type.

Start with GTM Alpha, because deal size and cycle decide the split between outbound and account-based work. Then ICP Intelligence names the roles in a 3PL buying group and turns champions and triggers into searches.

Revenue Enablement carries the account after the first contract. Discovery comes before the account plan and the ROI case because the ROI tool needs the buyer's own cost figure, and the discovery metrics questions are where that figure comes from. The steps are in the table alongside.

Step 1. Check which motion should lead new logos, and which should lead expansion

Input to the EPIC audit in GTM Alpha: last-mile routing and dispatch sold to 3PLs, retailers and manufacturers with their own fleets; Series A; ACV $36,000; a 75-day cycle; NRR 125%; 3,000 addressable accounts; deals mostly from outbound; India; current channels outbound, events and content; no self-serve.

What came back: Inbound and Outbound leads with 8 ("Series A starting point 6; Majority of deals from outbound (I +2)") and Ecosystem and ABM is second with 6 ("Series A starting point 5; India B2B (E +1)"). Product-Led Growth is "capped at 4". The NRR rule, "NRR above 120 percent (expansion working, amplify it)", added a point each to Community-Led and Product-Led Growth, not to Ecosystem and ABM.

Then I scored the expansion deal: the same inputs with $90,000 a year and a 120-day cycle. Ecosystem and ABM went to 10, with the reason "Series A starting point 5; ACV above 50,000 US dollars (E +2); Deal cycle above 90 days (E +2); India B2B (E +1)", and Inbound and Outbound fell to 7.

How to read it: one company, two motions. New logos get no points from the deal-size and cycle rules, so outbound leads. The expansion crosses both thresholds, so I work each landed account as an account-based programme. That split is my reading of the two runs.

Step 2. Map who decides in a third-party logistics company

Input to the buying group tool in ICP Intelligence: champion Head of Last-Mile Operations; known stakeholders COO, CFO, Head of IT, City Operations Managers and Dispatch Leads; $36,000 a year to start and $90,000 at full rollout; 3PLs delivering in 10 or more cities.

What came back: the roles in the table alongside and the proof this sector trusts: "a before and after of cost per delivery or first attempt delivery at one hub, measured over a full cycle of busy and quiet weeks."

How to read it: the economic buyer's objection, "our margins are too thin for this", is answered in step 6: "Tie the price to cost per delivery and failed deliveries measured in the buyer's own data, not to a general claim." The user row suggests "a pilot at one hub with an offline first driver app". Offer that only if your product has one.

One quirk: the tool filled the reviewer slot with the usual "Finance (checks the cost per delivery)", listed my CFO under "Also in the group (your input)", and called Head of IT "not in your list" after placing it. Treat the CFO as the finance reviewer. The CFO approves spend above $50,000, so the move to $90,000 brings a new approver into the deal.

Step 3. Find lookalike accounts by trigger, not only by firmographics

Input to the lookalike tool: third-party logistics, retail and consumer goods manufacturing; 201 to 5,000 employees; India; SAP, Oracle Transportation Management or Unicommerce; champions Head of Last-Mile Operations, Head of Logistics and Fleet Manager; and the four triggers in the table alongside.

What came back: searches for Sales Navigator, search ads, intent and contact databases, one signal per trigger, and the roles I left out: "Chief Operating Officer, Head of Supply Chain, Transport Manager, Head of IT". It "generates targeting CRITERIA, not actual data."

How to read it: the trigger signals need editing. The new COO signal watches for "A new Head of Last-Mile Operations or a related leader joined in the last 90 days", so add COO and Head of Supply Chain to the lead search. My additions are in the table alongside.

Before you run it, map my industry labels to Sales Navigator's own, and qualify on cities served and daily deliveries, because headcount is a weak guide to delivery volume. Keep one saved search per buyer type, because the champion title differs.

Step 4. Run discovery on the nine cities not yet live

Now the existing account: Example Logistics Co pays $36,000 a year for Lanehop in 3 of its 12 cities. Input to the discovery question bank in Revenue Enablement: MEDDPICC, Head of Last-Mile Operations at a 3PL; known pains "About 1 in 6 deliveries fail on the first attempt", "each city plans routes in its own spreadsheet" and "dispatchers spend hours re-planning routes when orders change"; and the gap "who signs the expansion beyond 3 cities, and what the CFO needs to see".

What came back: a "Gaps to fill first" section, a question on each pain, the MEDDPICC questions, and a close that asks for "a baseline on first attempt delivery rate before the next call".

How to read it: the metrics question in the table alongside feeds the ROI case in step 6, so leave the call with an answer and a name against it. Some lines read oddly because the tool puts the product name where a buyer would name the problem, for example "Which other vendors are you speaking to about Lanehop?". Say "about route planning in the other cities" instead.

The gap question the tool wrote covers only the signer. My gap had two halves, so I add a question of my own for the CFO half, not from the tool: "Above $50,000 the CFO approves. Which number would the CFO check first, cost per delivery or failed deliveries, and who in finance can give us this year's figure?"

Step 5. Plan the expansion around the peak season

Input to the account plan tool: $36,000 ARR, the five contacts, three expansion areas (the other 9 cities, one dispatch view across all 12, live re-planning), Competitor A pitching its suite to the COO, the city spreadsheets, and notes: the full rollout is about $90,000 a year, and the next peak starts in 10 weeks, when city teams freeze system changes.

What came back: a next step per contact, questions for each threat, and the dated plan in the table alongside. For two expansion areas, the other 9 cities and one dispatch view, it names the city operations managers as the likely sponsors; for live re-planning it says "ask the champion who would sponsor it". It is candid about its own tier: "By this tool's rule on ARR alone the account sits in the Growth tier with medium expansion potential; that is a rule on the number, not a view of the account."

How to read it: the plan runs to 22 January 2027, but ten weeks from 26 October is 4 January, so the decision would land inside the freeze. The tool asks you to "Check the dates in this plan against your own note above." My fix: agree the first wave of three cities in days 31 to 60, go live after peak, and use the peak weeks in the live cities as the busy half of the before and after.

Also replace the general CFO question ("Which finance numbers are late or reworked each period") with the CFO question from step 4.

Step 6. Build the ROI case the CFO will check

Input to the ROI business case tool: cost reduction, the expansion price of $54,000 a year (the step from $36,000 to $90,000), a current annual cost of $300,000 for failed first-attempt deliveries in the 9 cities, an expected improvement of 25%, the current process, and the three-city result: first-attempt failures down from about 1 in 6 to about 1 in 10 over two quarters.

What came back: the figures in the table alongside, at medium confidence because "the value comes from your own figures". A one-time implementation line of $8,100, marked as an example, is left out of the ROI and payback.

How to read it: at 25% this case is thin. A 39% ROI sits well under the tool's example threshold of "100% considered strong", and the conservative case is negative. The 25% was a guess, and the tool says what it did not use: "Not used in this calculation: the current process and known metrics you supplied". The account's own three-city result, from about 17% to 10% of deliveries failing, is roughly 40% fewer failures (my arithmetic). Moving to a figure the account has measured is not the same as raising it to make the case work.

At 40%, with every other input the same, ROI became 122%, payback 5.4 months, and the conservative case stayed positive at 11%. Both runs are in the table alongside. The 40% is still three cities' result applied to nine others, so ask the COO whether those cities are alike, and ask finance to price the dispatchers' re-planning hours, which neither run counts.

One line to read past: the sector notes use freight words such as shipment and consignment. With a last-mile buyer, keep to cost per delivery and first-attempt delivery.

1. Run the EPIC audit twice, at your new-logo deal and at your expansion deal.
2. Map the buying group for each buyer type, and find out who approves spend above which amount.
3. Build one saved search per buyer type, add the leader titles your triggers need, and put the peak-season planning date for each target account in your CRM.
4. For every landed account, run discovery on the cities not yet live and leave each call with a baseline and an owner for it.
5. Build the ROI case only from the buyer's figures, and include the result from the cities already live.

1. Selling the expansion as an upsell. A larger contract brings a new approver and a new competitor; plan it as a second sale.
2. Ignoring the peak calendar. A plan that ends inside the change freeze waits for the peak to pass.
3. Pitching features to an operations buyer. Lead with cost per delivery and first-attempt delivery in their numbers.
4. Choosing the improvement percentage to make the ROI work. Use the measured result from the live cities.
5. Treating 3PLs, retailers and manufacturers as one search. The champion title and the reason to buy differ.

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