So is this really an AI problem anyway...?
What makes for a good consultative approach?
Clients want to talk to experts to get the best possible advice. This is particularly the case with new technology. As each new transformative tech comes along, there’s a feeling of ‘I think I should be doing something about this, but I’m not quite sure what’.
This nagging doubt can start to feel overwhelming. Digital ad buyers and publishers today are operating in environments where they’re swimming in data (sometimes drowning), which is generated from the many digital touchpoints as audiences switch from device to device, from channel to channel. There’s only so far humans can manage this scale and complexity. At some point, only AI can take this further.
However, not all problems require AI solutions. Those that do are around large, complex, fast-changing data sets. Those that don’t are usually less complex, smaller in scale, involve less change, or don’t require prediction.
Our CEO and co-founder Rael Cline puts this succinctly in ExchangeWire: “If you’re saying that every challenge needs an AI solution, then why can’t it help you find your socks in the morning, and why do you still have to feed the cat every night?”
He goes on to explain how to tell when you have a business challenge that requires an AI solution, and when you do not - that is, when a rules-based approach might be better. We summarise this in the table below:
And this is where the consultative approach comes in: we have actually advised prospective clients that they don’t even need AI to solve their problems.
That, we feel, is the ultimate in impartial, professional consultancy. The very best advice can sometimes be: you’ll get a more immediate return on a different investment.
You can read what else Rael has to say over at ExchangeWire: Can AI Really Solve Your Problems.