There are only 2 types of advertising – but what they are depends on who is talking.

One basic distinction is between (a) direct response and (b) everything else.
Another is between advertising that (a) works and (b) doesn’t.
A third is between advertising (a) investment and (b) cost.

The legendary Dan Kennedy teaches that s/he who can spend the most to acquire a customer wins in the end.

That’s may be true, insofar as it goes. But it’s not the whole truth.

If the ability to acquire the customer depends solely on the amount spent on acquisition, then whoever is willing to spend the most will win more customers.

There’s no guarantee however that those customers will be profitable or viable.

If you and I are competing for the same customers, and I can acquire mine at a lower cost than you then, all other things being equal, I will win.

To have a viable customer base, I need to know a few crucial averages:
1. The cost of acquiring a customer
2. The annual sales value
3. The annual gross profit
4. The other costs of fulfillment & customer service
5. The customer lifetime.

E.g. my average customer spends €1,000 a year with me. My gross profit is 35% and my other costs are €50 p.a. giving me an annual contribution of €300. My customer lifetime is 3 years so the lifetime contribution is €900.

If I am willing to spend €900 to acquire a customer, I will break even over time. However, it would be a foolish and overly optimistic entrepreneur who would consider investing more than 1 year’s contribution to acquire that customer.

So it’s less whoever can afford to (or is willing to) spend the most to acquire the customer who wins than whoever can afford to (or is willing to) spend the most to acquire the customer while remaining profitable that will win.

Few companies advertise effectively. If you doubt this, pick up any newspaper or magazine, look at any tv channel, social media or other website that carries ads. The majority of ads suffer from one or more of the following fatal flaws:
(a) boring
(b) unbelievable
(c) unclear
(d) irrelevant
(e) annoying

And it gets worse.

Even with a clear call to action and simple, easy to follow instructions most ads fall into the ‘cost’ category instead of the ‘investment’ stable.

For an ad to meet the criteria of an investment, several things must be defined prior to running the advertisement:
1. The purpose – what is the objective of the ad, what specific action do I want the prospect to take.
2. The cost – how much am I willing to invest? Is this a fixed or variable sum?
3. What is the value of success? What level of sales do I need to breakeven?
4. How will I measure my results?

Sadly, many advertisers spend money on ads that have at least one fatal flaw and without meeting the necessary criteria.

And it gets even worse.

Imagine creating an ad that avoided the killer mistakes, that met the criteria but still failed to make it an investment…

How could that be? Surely if the spend didn’t result in sales or profit but yielded valuable data, it could count as an investment?

Possibly, yes.

But the error isn’t failing to collect valuable data. Instead, it’s usually hiding in a murky space – the one where data of a single type should be, but where in fact the data are mixed. And because of this, I cannot know for sure what the result of my campaign is.

I was engaged by a client to review his operations, particularly his sales and marketing. He had recently lost his largest customer, a blue chip company that accounted for 40% of his turnover. In among the weeds, I discovered he was spending more than €1,000 a month advertising with a local newspaper. When I asked what proportion of his sales this spend generated, he didn’t know. Nor was it possible to know because his ads and campaign were not designed to capture or yield that information.

I suggested a few minor changes to his approach, the most important being a unique telephone number, listed only in those ads. Over the remainder of the contract, we tracked the precise response and used this to test different offers. While we did improve the results (not too hard when your starting point is €Zero) the return never approached the cost. Terminating the contract freed up €15,000 a year to fund more precise and measurable campaigns.

We tend to think of Big Data as something Google, Apple, Microsoft or some other digital behemoth gathers and surreptitiously analyses to magically penetrate our secrets and understand our motivations.

I suggest big data is any set too big to hold in your mind at a sufficient level of detail to make it useable. By that definition, the information we collect on our advertising campaigns would be classed as big data. And because of that, more often than not we don’t actually analyse it at all. We take it to mean what we first think it means, whereas interrogating the data might yield a very different understanding.

The net result of this is jumping to conclusions – often wrong conclusions – by continuing ad spends that should be killed and killing campaigns that should be scaled.

The moral of the story is we need to do our homework first, not last. Invest the time, attention and energy in preparing before committing the cash. Know precisely what you want to achieve, how you’re going to measure results and what results you need to justify further spend.

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