Can AI be ‘Creative?

Can AI be ‘Creative?

 

Marketers have outsourced creative development to specialists from the beginning of media advertising in the late 1800’s. Correctly, there was a realisation that it was a specialist skill, not easily found, nurtured, and leveraged.

Amongst the daily advertising dross have been creative gems that have built great brands. At least they were great for a while before stupid management cut the creative advertising budgets in favour of short-term sales activation, a quantitative dead end.

Over the last 8 months another monster has emerged, and suddenly the conversations I hear about are all how to get A.I. to do your creative for you, and save a heap.

Well, here is the news: It cannot.

AI should be called EI. Enhanced Intelligence, not Artificial. All it does is build on what we already have, make connections, do drafts, take what has happened in the past and extrapolate.

Creativity has no role in AI, at least not yet.

Would AI have come up with the great 1964 Volkswagen  “Snowplough‘ ad, the one voted the best ad of all time by the Cannes panel? Could AI have maintained that creative standard culminating in the 2012 Darth Vader series?

If there was anything that pushed the disastrous Volkswagen software rort off the front pages, it was this 50 years of brand equity built up by the brilliant, creative advertising.

A.G. Laffey when CEO of P&G recognised that the creativity had been stifled by the rules set in place by a right brained organisation. As a result, everything was stale and boring, as were P&G’s results. He removed the quantitative hurdles, and challenged their agencies to break the rules they had previously been bound by, and demanded that P&G marketing personnel became less risk averse. A new age of creative advertising supported by a tsunami of new products emerged. P&G doubled in size from the early 2000’s, $US44 to 85 billion revenue, increased margins, and earnings/share increased fourfold.

A few months ago in a SME workshop that had a decidedly older demographic, every person in the room knew the brand when prompted by: ‘you ought to be congratulated’. It is 35 years since Meadow Lea was advertised using that piece of creative genius.

Could AI have come up with that?

 

Header cartoon credit: Gapingvoid.com

 

The biggest challenge for every dreamer who aspires to be an entrepreneur.

The biggest challenge for every dreamer who aspires to be an entrepreneur.

 

 

Many of the impediments to starting a new business have been removed over the last 20 years.

You no longer have to hire an accountant to register the business, hunt around for premises, hire a bookkeeper, find an advertising agency, build a product prototype, spend days designing the letterhead, understanding the regulations and weaving your way through them, and doing the hundreds of other tasks necessary to start a business.

They can all be done with digital tools from your kitchen table, or outsourced to someone who has the specific expertise necessary, from their kitchen table.

What used to take time, money and most importantly the energy of budding entrepreneurs can no longer be used as an excuse for not moving forward.

The wheat has been sifted from the chaff by the digital winds.

That just leaves the toughest challenge, the one that in most cases motivated the thinking in the first place, the one that separates the dreamers from the ‘doers’.

How do you identify and generate traction with those prepared to part with their money to buy your product or service?

When they have bought from you once, how do you keep them coming back, or better still, turning your product into a subscription service?

This always was the hardest part of the entrepreneurial journey.

It always will be.

However, these days there are far less excuses not to have a go than there were 20 years ago.

 

 

The marketing “C-word”

The marketing “C-word”

 

 

Context. The word is ‘Context’

Marketing is a fundamental contributor to our commercial lives.

It is about defining and leveraging the value you create for another, for which they are prepared to pay, while not being about the transaction.

The beach and Heineken experiment as told by behavioural psychologist Richard Thaler describes beautifully the importance of context.

Two blokes on a beach, very hot, and desperate for a beer.

If they are told there is a shack a kilometre down the beach from which they can buy a Heineken, how much would they pay for the beer?

Same situation exactly, except the shack becomes a 5-star hotel.

The price they are prepared to pay for a Heineken from the 5-star hotel is roughly double the price they expect to pay for the same product from the shack.

This is a classic case of context and expectation; people expect to pay more for the identical product from the 5-star hotel than from the shack.

The utility they get from the beer is identical, only the context of the purchase is different.

How do you leverage the context in which your product is presented to potential customers to maximise your revenue generation?

 

 

 

My website ‘Vegemite’ test

My website ‘Vegemite’ test

 

 

When my kids dropped a piece of toast, or bread on the floor (almost always spread side down) we used to invoke the ‘3 second test’. This was simply that the bugs took three seconds to wake up and realise there was a feed nearby, so if it was retrieved inside that time, it was OK to eat.

Same with a website, almost.

We are all busy, our attention is stretched beyond reasonable limits, and we have no time to waste. So, when your potential customer is researching, or just loitering on the web, you have perhaps 3 seconds to engage them, such that they have a closer look.

In those 3 seconds, you must communicate three things if you are to get them to pay you any of their scarce attention:

  • What problem you solve.
  • Who do you solve it for.  In effect, a written ‘elevator speech’, what you do and why they should listen.
  • Call to action. What you want them to do next.

Pretty obvious?

Give yourself 3 seconds to look at most websites, and ask yourself those three simple questions.

How does yours fare?

PS. For my readers outside Australia, ‘Vegemite’ is a spread for bread and toast we Aussies are brought up on, which the rest of the world thinks looks and tastes like old axle grease.

I bet every ‘Matilda’ has it almost every day!

 

 

When does a forecast become a prediction?

When does a forecast become a prediction?

 

 

Our corporate culture demands that we forecast outcomes in the early stages of almost any project.

Accountants feed on the IRR numbers, and these outcomes find themselves incorporated into all sorts of budgets for which people are held accountable. They change from being a forecast, an assessment of what might happen given a set of assumptions, to become a set of predictions, upon which people careers have become dependent.

Not a good outcome for building a culture that is supportive of innovation, which by its very nature is risky.

Prediction and forecast are often wrongly used as similes.

A prediction is a statement of what will happen.

The sun will rise tomorrow.

A forecast is a statement of what the forecaster believes will happen. It will be subject to all sorts of variables and new information, but it is the best guess given the circumstances.

I have written many business plans that included forecasts, my best guess at what the future would look like. Those best guess forecasts then tend to become the targets, against which performance was measured. This has usually resulted in a balancing act between the IRR numbers, and the forecasts being as low as possible to get a guernsey. Neither is a healthy way to make resource allocation choices.

If you want a prediction about the future, go to the local fair and pay somebody with a crystal ball to tell you. If you want a forecast, find someone who has records, and a routine that updates those records on a fixed timetable, adjusting as they go.

I strongly encourage all my clients to do a weekly 13 week rolling cash forecast. What always happens is that over time, the forecast of the weekly cash balances become increasingly accurate as the many variables become better defined and understood.

Often it is a matter of the choice of words.

Current governor of the Reserve Bank, Philip Lowe chose to set a specific time frame around his forecasts relating to interest rate rises when he said in March 2021 that ‘the cash rate is very likely to remain at its current level until at least 2024‘. This forecast  became a prediction upon which people based their decision to buy a house. After all he is the Reserve bank governor so should know.

Had he just altered his words a little to be more specific about the caveat contained in the term ‘very likely’ to something like: ‘the odds are that interest rates will hold steady for some time‘  it would have remained a forecast, and he might have retained his job when it come to the end of his current contract in September.

For what it is worth, in my view, he should retain his job. He is a talented, experienced and highly qualified economist, not a political wordsmith.

Addendum. Within an hour of publishing this post, it was annpounced that Philip Lowe was to be gone. No extension, pick up your money and go. Nice words all round about how great he was, but piss off, here is the gold watch, go away.

The irony, at least it is to me, is that the current deputy has been appointed in his place. Irrespective of the qualities of the deputy, the job description calls for a culture change in the reserve. Appointing someone to lead that change who is now top cocky because they were able to leverage the existing culture to their benefit is an utter nonsence. A failure of any understanding of the basics of leadership and culture change.

For me, it evokes visions of deck-chairs and icebergs.

 

The good and bad of AI impact on SME’s

The good and bad of AI impact on SME’s

 

 

 

Anyone who reads my stuff on any sort of regular basis will know I have been deeply engaged with the potential impact of AI on all of us, since I stumbled across ChatGPT in early December last year. Of particular interest is the apparent potential for efficiency gains, particularly amongst the SME manufacturers I serve.

On one hand, I have been excited by the potential of AI to generate efficiency and expand the operational scale of SME’s. On the other, scared shitless at the potential for bad actors to sneak into our collective pockets and steal everything.

I need to write to think.

It forces me to sort out the stuff swimming around between my ears, as when I can articulate it sufficiently to write about it in some coherent manner, it leads to some level of understanding.

So, here is my list of the good stuff, followed by the bad, as it relates to the core of my business: strategy and marketing, starting with SME’s and the written word.

The good things AI can do for you.

  • Summarising large blocks of copy, even when it seems very messy.
  • Brainstorming; ideas, subject lines, complementary ideas, headlines.
  • Editing and grammar. (I have been using the editing and ‘speak’ functionality of word for years, it is essential to me, and is AI that we now just treat as part of the furniture)
  • Assembling descriptions and fact sheets
  • Looking for logical holes in an argument
  • Repurposing copy from one platform to another
  • Research
  • Outline and first draft.
  • Translation and transcription

The stuff AI is no good at doing.

  • Humour
  • Reflecting current news and events
  • Factual reliability. (Sometimes, it just makes stuff up)
  • Finding a good metaphor
  • Being creative. The great irony with creativity is that AI opens a whole new set of what is possible with visual tools, which can then combine with verbal cloning tools to completely alter apparent reality.
  • Looking ahead
  • Breaking complexity down to ‘first principles’
  • Pouring another glass when faced by a blank page and a deadline.

Then there is all the other stuff AI will do, and evolve to do in the very near future, that is not writing. Graphic design, integrating currently separate digital systems (API’s on powerful steroids) identifying trends and holes in huge masses of data. The impact on medical technology is already profound. When the human genome was first successfully mapped in 2000, the cost of that first success was in the tens of billions of dollars. Now you can send away a sample and have it returned with your genome map for a few dollars overnight.

The key it seems, is to be very good at explaining to the tool what it is you want, in the detail a 5-year-old will understand. As the header cartoon illustrates, being human while driving this stuff will rapidly become the differentiator.

Header credit: GapingVoid.com.