Out-of-home entertainment

Out-of-home entertainment (LBE) operators are gradually making the shift from running their business by gut feel to making data-driven decisions. The next evolution of this digital transformation is operators developing a 360-degree guest experience design strategy.

But for the most part, each operating activity is still being understood in isolation. Google Analytics might be providing website traffic numbers, social media channels measured by engagement, weekly takings tabulated at the POS and machine levels by the card system, and a loyalty database tracked by a tool like Mailchimp.

When done well, operators take an experimental approach to improving each of the activities they’re measuring. If you improve a bunch of variables, somehow the business will grow, right?

The problem with siloed measurement, however, is that it does not answer the question whether $10,000 of online advertising, or $10,000 of new amusement machines, $10,000 of CSR training, or $10,000 of loyalty incentives is going to yield the best bang for the buck.

In other words, how do you actually use all this data to grow your business and make informed investment decisions?

A starting point for creating a unified set of business KPI may come from cross-pollinating the unit economics of an online video game or service: where lifetime value of a customer (LTV) is measured by acquisition * monetisation * retention.

If you have 1,000 customers, who spend $20 per month, and stick around for 3 months on average, your gross takings are $60,000.

Tweak that a little, and a workable formula for an LBE operator emerges: # of unique guests * average spend per visit * average visits per quarter.

Given that these are multiplicative factors, and that there will be diminishing marginal returns on any of them over time, the answer to the $10,000 question is, probably, “the weakest link of the three”. But you won’t really know until you can actually make apples-to-apples comparisons.

This approach becomes more useful when you dig deeper. For example, by associating a Cost of Sale to each factor: your acquisition cost per user (marketing spend / new customers), your net revenue (gross – redemption & other variable costs), and retention costs (loyalty discounts, perks).

Another useful view is working out the anti-data: your churn at each step of the guest lifecycle. What percentage of social media and web visits are not resulting in customers appearing at your doorstep? What percentage of guests are leaving after their visits without transitioning into your loyalty programs? And, finally, what percentage of guests in your loyalty program do you never hear from again? The answers to “why not” questions raised by painful anti-data are undervalued in many OOHE operators’ decision-making.

The guest lifecycle is only top of the pyramid. Clearly, there’s a lot of data kung-fu to be done to arrive at like-for-like multipliers. But the odds are, any operator sweating away improving isolated data points, making apples-to-oranges investment decisions, still has some work to do on their framework for understanding their guests’ lifecycle.

Guest experience design across digital & physical assets, and defining the correct corresponding KPI to track,  is tricky. Our team is available for a chat, for operators ready to start understanding their acquisition, during-visit, and post-visit metrics through a shared set of KPI’s.