Pizza Hut Israel was running its customer relationships through several separate systems. Each one created its own version of the customer — different touchpoints, unsynchronised timing, contradictory messages, even different language. The behavioural data existed but was effectively unusable.
Pizza Hut is known globally as a destination for pizza lovers, and its offline performance reflected that. Online was another matter. To move the bottom line, the brand needed its digital relationship to match the strength of its physical one — which meant consolidating every touchpoint into one system that could act on what a customer had actually done.
Brands speak to customers across many platforms. Nothing matters more than saying the same thing in the same language throughout. We brought every point of engagement under one roof so each interaction could be controlled and coordinated.
Every customer has different motives and expectations, which is why they behave differently with the brand. Content, coupons and messages were tailored per customer against their own expectations — the basis of a deeper relationship rather than a louder one.
Tracking current and prospective customers across every channel in real time, so the right message could land in the right place at the right moment rather than on a fixed schedule.
Defined with Pizza Hut: raise engagement, strengthen brand loyalty, grow the members club. The premise — customers who receive personal, relevant content become customers who return — drove a marketing automation approach that weighed every channel the customer had touched: recent purchases, recent visits, click and open behaviour.
Our studio team worked with Pizza Hut to create a new design language across all customer-facing marketing content.
The biggest single shift: away from mass discounting toward laser-focused, real-time, personal offers matched to each customer's purchase history and engagement. Attractive because relevant, not because deep.
Moving from manual work to automation. Each automation had its own rule set and trigger; once a customer entered one, it branched according to how they responded to the previous message. Built after a period of audience segmentation, so the eight covered every customer type touching the brand.
Four quick stages, one join gift. Every new subscriber to the Pizza Hut Members Club entered it automatically. That single automation doubled the number of new club members — the clearest illustration of the whole thesis: the right message, triggered by real behaviour, at the moment intent is highest.
The “Let's be friends” welcome automation doubled new club signups.
Customers who abandoned their basket online were brought back and converted to purchase.
Higher open and click rates across the programme following segmentation and personalisation.
Every business differs. This case describes how our team consolidated systems and built the automation programme — not a promise of identical outcomes.
Pizza Hut's problem was fragmentation. Yours might be deliverability, a flat repeat rate, or automations that were built once and never revisited. The starting point is the same: find out what's actually happening before changing anything.