Real Brands. Real Gains. Real Proof.

GlobalPay’s existing legacy marketing-automation setup – Gamooga – was sufficient for the business requirements at the time, particularly when the organization was primarily focused on its B2B-led model. The platform supported the team’s core communication and automation needs, and there was no immediate need to replace it simply for the sake of changing technology.

The business, however, began shifting its focus toward direct-to-consumer (D2C) growth. This changed the role marketing needed to play. Instead of primarily communicating with known customers and partners, GlobalPay needed to engage consumers across their journey – from a rate check or currency-order initiation to a remittance drop-off, card interaction, or other high-intent action.

That shift created a new set of requirements: real-time customer data, unified omnichannel engagement, behavioral triggers, a single customer view, and a direct connection between marketing intent and the sales team.

The question was therefore not simply about replacing an existing automation tool. It was about finding a reliable technology partner that could support GlobalPay’s next phase of growth – one that could integrate with its existing ecosystem, bring data and engagement together, scale across D2C channels, and evolve alongside the business.

This was the point at which GlobalPay partnered with Netcore, with the objective of building an engagement infrastructure designed not just for automation, but for real-time, customer-led D2C growth.

Just as important, the Netcore team took ownership of GlobalPay’s engagement outcomes rather than just shipping a build – treating GlobalPay’s KPIs and growth as its own, staying close through discovery, integration, and go-live, and steering decisions instead of waiting to be asked.

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Hirsch’s sells experience goods – things people take time to buy. A fridge, a television, a lounge suite. Customers compare products over days or weeks, leave the site, and come back when they are ready, a pattern Hirsch’s own journey data confirms. Email is what brings them back. If a campaign is not seen, the customer who was close to buying simply does not return.

By this point Hirsch’s had a mature email programme behind it: engaged audiences, relevant campaigns and healthy delivery. The opportunity was no longer about sending better emails. It was about making sure more of those emails were seen.

The brief for the channel was direct:

• Increase email open rates
• Improve customer engagement with campaigns
• Drive higher click-through rates
• Generate more revenue from campaigns already being sent

Delivered is not the same as seen

By every measure the team had, the email programme looked healthy. Delivery rates were high. Bounces were low. Nothing on the dashboard pointed to a problem.

But a significant share of Hirsch’s marketing emails were landing in the Promotions tab rather than the Primary inbox. An email that reaches the inbox but receives limited visibility has significantly less opportunity to drive engagement.

The scale of that is easy to underestimate: 68% of users rarely or never open their Promotions tab (Netcore Email Benchmark Report 2026). For most brands, that is the majority of a campaign’s audience, gone before the subject line has a chance to work.

The problem stayed hidden because the reporting looked fine. Delivery only confirms that an email arrived. It does not tell you whether anyone saw it. That difference is where the channel was losing its return, and no standard email report is built to show it.

The team had already worked the obvious levers – creative, timing, list practice and standard deliverability best practice. Performance barely moved, because none of those levers change where an email lands. And the gap widened at the worst possible time. During major sale periods, every retailer’s volume rises at once and the Promotions tab becomes the most crowded place in the inbox. The one time Hirsch’s most needed to be seen was the one time it was hardest to be seen.

A large share of redBus’s lifecycle email was landing in Gmail’s Promotions tab rather than the Primary inbox – buried, in practice, since that isn’t where travellers look first. The campaigns themselves were strong. What wasn’t keeping pace was their visibility: Gmail’s classifier wasn’t reading the relevance and engagement signals around those sent the way the content warranted, so fewer travellers saw the email in time to act on it.

The baseline carried the same story. Before any changes, the programme was opening at 22.00% with a 0.03% click rate on delivered email – below what its reach and relevance supported. Both teams agreed to go after the cause rather than patch around it.

AJobThing ran a high-frequency email programme across both audiences – employers and job seekers – but the team was making send decisions with limited visibility into what actually drove performance. Before Insight Agent, every performance review meant manually cross-referencing exports to compare one week against the next – a slow process that left little confidence in the picture it produced, and no early warning if the channel itself was starting to strain.

Campaign Intelligence Blind Spots

• Week-over-week comparisons: Comparing performance across Open Rate, CTR, Delivered, and Sent meant pulling and reconciling exports by hand, which made it hard to spot patterns quickly.
• Assumption over evidence: Send decisions ran on assumption rather than historical engagement data – the team couldn’t say with confidence which content, which segment, or which send time performed.
• Send-time guesswork: Optimal send times were hard to isolate, so scheduling ran on habit rather than evidence.
• Invisible content performance: Without a content-type view, the team couldn’t tell a Promotion send from a Hiring Kit send in performance terms.
• Undetected audience fatigue: Early signs of audience fatigue went unnoticed until unsubscribes had already climbed, putting sender reputation and domain deliverability at risk for every future send, not just the one that caused it.

To protect that reputation and get more out of every send, AJobThing needed a way to turn raw campaign metrics into fast, actionable decisions – without adding manual overhead to get there.