Solomon
Salako

The Problem

Affiliate placement decisions were being made on instinct - which retailers felt right, which rates were highest, which categories were trending. There was no scoring model, no audience-fit validation, and no seasonal allocation logic. Revenue was inconsistent as a result.

The Framework

I built a retailer scoring model that weighted commercial rate at 60% and demographic relevance at 40% - deliberately structuring it so that rate alone couldn't win a placement without audience fit. The model included:

• Category clash validation process to prevent cannibalisation between adjacent retailers in the same placement window.
• Seasonal allocation framework built from Q4 transaction data, mapping which categories over-indexed in which periods and pre-assigning placement priority accordingly.
• 500+ retailers scored and tiered across 25 categories, with conquest mappings identifying which retailers were most likely to convert against WeShop's active user segments.

The Commercial Logic

The most important design decision was the 60/40 weighting. A purely rate-driven model would systematically favour unfamiliar high-commission retailers over trusted lower-commission ones - exactly the wrong trade-off for a platform where user trust is the core product. Rate as a tiebreaker, not a primary signal, was the principle that made the model commercially sound rather than just financially optimised.

Results

£2.91M cumulative revenue over 18 months. Monthly peak of £260K+. CTR improved 25% against pre-framework baseline. Placement conversion improved 15%. The framework is now the operating model for all affiliate decisions - not a one-off exercise.

The Starting Point

The commercial team believed low merchant activation was driven by fraud prevention concerns. The existing positioning leaned into security and protection. I wasn't convinced - so before committing to a GTM built on that hypothesis, I designed a research programme to test it properly.

The Research Design

15 structured interviews with active and lapsed merchants. Deliberately designed to stress-test the fraud hypothesis, not confirm it. The interview guide avoided leading questions and created space for merchants to surface their real objections unprompted.

• The fraud hypothesis was largely absent from merchant concerns. What surfaced consistently was attribution confidence - merchants couldn't justify the affiliate spend to their own finance teams because they couldn't see what WeShop was driving.
• The language merchants used was specific and consistent enough to build positioning around directly - not interpreted, transcribed.
• Synthesised findings into a positioning brief that reframed WeShop's merchant value proposition around measurable attribution, not protective security.

From Insight to Execution

Rebuilt the onboarding sequence around the attribution confidence insight. New messaging led with transparency on how transactions were tracked and attributed - not with cashback rates or partner network size. Battle cards and objection handlers were rewritten around the real objection, not the assumed one.

The research findings also went to the product team. Transaction verification was elevated to Q2 roadmap priority as a direct result - closing the gap between what we were promising in positioning and what the product was actually delivering.

The Outcome

Activation moved from 20% to 45%. Renewal rates increased 15%. The more significant outcome was structural - the business now had a research methodology it could repeat, and the product roadmap had a commercial brief attached to the next development cycle.

What I Learned

The most dangerous assumption in positioning is the one everyone agrees on. Fraud prevention felt intuitively right to the commercial team - it was coherent, it was defensible, and nobody had tested it. Research designed to confirm finds confirmation. Research designed to challenge finds the truth.

The Challenge

WeShop's NASDAQ direct listing was a first-of-its-kind moment for a B2C rewards platform. The GTM had to work across two audiences simultaneously - retail investors and existing users - while operating inside SEC compliance constraints that limited what could be said, when, and how. There was no playbook for this.

The Approach

I designed a three-phase programme: pre-listing momentum, listing-day activation, and post-listing community amplification. Each phase had distinct channel mixes, message hierarchies, and compliance checkpoints.

• Authored the press release and investor narrative, framing WeShop's equity ownership model as structurally incomparable to traditional cashback - a deliberate repositioning away from the crowded rewards market.
• Built the eight-channel execution plan across email, push, social, earned media, community, in-app, partner, and UGC activation - each with separate cadence and compliance sign-off.
• Developed the user-facing communication strategy to convert existing users into informed holders, not passive recipients of a corporate announcement.
• Coordinated the Forbes placement as part of a broader earned media approach, not a one-off pitch.

What Made It Work

The decision to separate the investor narrative from the user narrative - and then reconnect them at the listing moment - created a coherent story that worked for both audiences without diluting either. The 7.54% email CTR reflected how well the user-facing message landed. The 4,580 UGC posts post-listing reflected genuine community energy, not manufactured engagement.

What I Learned

Compliance constraints are a forcing function for clarity. Every sentence that couldn't be said pushed the work toward what could be said more precisely. The best-performing creative in the campaign was the simplest - the pieces where the constraint removed all the noise.

The Problem

WeShop was competing in a market where TopCashback, Quidco, Rakuten, Ibotta, and Upside all positioned primarily on cashback rate. The implicit assumption was that WeShop needed to compete on the same dimension - and win. The strategic problem: competing on cashback rate is a race to the bottom against platforms with larger partner networks and more negotiating leverage.

The Intelligence Work

Benchmarked all five competitors across messaging, value proposition structure, merchant acquisition positioning, and consumer-facing narrative. The finding was consistent across all five: every competitor led with rate as the primary hook. Not one positioned on ownership, equity participation, or long-term value accumulation.

• Rate-led positioning creates a commodity market where the platform with the highest cashback wins - and WeShop would not win that fight at current scale.
• Equity ownership - WeShop's genuinely distinctive structural feature - was either buried or entirely absent from consumer-facing messaging.
• The opportunity was not to beat competitors on their terms but to change the terms of the comparison entirely.

The Repositioning

Built the case for repositioning WeShop not as a better cashback platform but as a fundamentally different category - one where shopping builds equity in a publicly traded company. This frame makes rate comparison irrelevant: you cannot compare equity ownership to a cashback percentage because they are not the same type of value.

Produced battle cards and objection handlers built around this frame, specifically addressing the moment when a merchant or commercial conversation defaults to cashback rate comparison. The objection handler sequence reframes rather than defends - moving the conversation from rate to ownership value before the comparison can be made.

The Outcome

75% adoption across commercial teams. The repositioning frame became the default language across partner acquisition, merchant onboarding, and press materials including the NASDAQ listing narrative. The equity ownership angle that appeared in Forbes coverage and drove the 400%+ stock surge on listing day was a direct output of this intelligence and repositioning work.