We were having a conversation with the CMO of a chain restaurant and discussed the need – and use – of data science. This CMO was referred to us from a very trusted colleague who also understands data science, so we knew the conversation wasn’t going to be an educational seminar on our behalf. The conversation went like this:
Us: Data science is a guaranteed eventuality because of the benefits it brings
CMO: We agree. The ROI from data science is very clear and we need to figure out how to get going down that path
Us: Don’t get us wrong, I think there is a spot for certain tools, and some might never be replaced. But the industry needs to demand more from current providers. Customers are just totally unaware of what’s possible so the bar is very, very low
CMO: Yes, we admit we spend way too much time wrangling tools and their providers. The industry too easily buys into the status quo without giving much thought for how tools and processes might be improved
Us: How do you think about budgeting for data science solutions? Does an existing solution need to be thrown out or is it a new budget item?
CMO: That’s a very insightful question. I think, ideally, we wouldn’t need new budgets because our existing tools should fill the void. But obviously that isn’t happening. So if the ROI is justified we would find a new budget for data science
Us: Does that mean you will continue to buy existing solutions?
CMO: It depends what they’re doing. If there’s too much overlap, maybe 80%, it’s going to be really hard to justify using a legacy provider that’s not as accurate nor as quick in delivering actionable information
Us: What comes to our minds is reporting. Most reporting tools are just lengths of rope long enough to hang yourself. The reporting isn’t telling you what to do and expects that you’ll come away with the right conclusion
CMO: I was thinking the same thing, especially given what’s possible. There could be instances where someone on our team needs to look at data a certain way, and if the use case is important enough we might keep subscribing to the reporting tool, but we’d really expect the reporting provider to step up their game and solve problems outside of the fringe use cases
Us: So it sounds like you’re thinking about data science as a new budget item that maybe goes away when existing solutions upgrade?
CMO: That sounds fair. We wouldn’t want to miss the opportunities data science brings now, but would be reluctant to consider solutions that aren’t at that new standard going forward
This was useful dialogue if for nothing else because it shows how merchants need to be thinking about budgeting for new solutions. This is almost certainly not a novel phenomena: new solutions have come and gone over the years while salesmen eagerly sought budgets to sell against.
What incumbent providers need to take from this conversation is that their customers are only going to accept lackluster products for so long. Too often providers put minimal efforts into building solutions. Too often providers neglect investment in their own products so they can buy themselves that new car (i.e. every POS company that refuses to invest $20K in data replication to create cloud connectivity).
The bar for acceptable value is going to be raised across all product categories as data science makes drastic improvements to business outcomes. Just like you can no longer buy cars without headlights and windshield wipers, soon enough customers will no longer consider solutions that aren’t using data science, or aren’t actionable.
Once you get a taste of the good life, it’s really hard to consider anything else.