The times are not far when the above AI disclaimer will be a thing of the past.
As AI continues to challenge, transform, and enhance old ways of doing things, a lot of print and digital content will be conceptualized and written with minimal human intervention. Till then, let’s continue to experience the joy of putting human thoughts on paper.
One area where artificial intelligence (AI) has revolutionised the way we do things is innovation research. Companies like Ipsos have been at the forefront of combining AI with human intelligence (HI) to give more compelling solutions to client questions around launching successful innovations.
The blueprint for success hasn’t changed. Innovations that address an inherent consumer need (relevant innovations), are different from those already available in the market (the uniqueness of the proposition) and are priced right (expensiveness perception), have a better chance of succeeding than those ideas that are weak on these elements.
Combining AI with HI will help clients conceptualise relevant, unique, and appropriately priced propositions. But there are many more advantages to integrating AI into the process.
Democratisation of consumer feedback
Historically, large corporations have invested significantly in consumer insights that help them either fine-tune new product launches, modify the proposition, or, in some cases, completely drop the launch idea owing to a lukewarm consumer response.
These companies have full-fledged consumer insights teams that ensure new product launches are backed by real consumer feedback.
This contrasts with relatively smaller companies and brands that have a lot less budget to spend on market research. In a lot of these cases, companies would launch their innovations based on their own understanding of the market or, at times, their ‘gut feel’. This meant large companies had a better chance of launching a potentially successful innovation, given their investments in market research.
With the advent of AI, this gap between ‘haves’ and have-nots’ related to research budgets has diminished. An AI+HI-driven innovation research is likely to cost a lot less than a full-fledged traditional innovation test that does not incorporate AI. This means even smaller companies with less money to spend on innovation research can benefit from this integrated approach, thereby creating a more level playing field for all in the fray to launch new products in the market.
Shortening of the feedback process
One of the biggest challenges of the insights industry over the past decade has been the speed with which consumer insights are fed into the client’s innovation cycle.
An elaborate exploratory work to identify unmet consumer needs at the beginning of the innovation cycle and an extensive screening & testing of multiple propositions for a potential launch could take between four to six months.
With AI complementing HI, this feedback process could be shortened to seven to eight weeks; without losing out on the robustness of the research process.
A shorter research cycle means not only savings on time but also significant savings on investments since the use of AI would help answer business questions with fewer projects.
Shortening of the innovation cycle
A typical innovation cycle would start with knowledge curation using existing assets, discovering innovation space and unmet needs, generating ideas, concepts, products, packs, and finally the full mix.
These would also include the testing of stimuli amongst consumers (ideas, concepts, and packs) in-between. This entire cycle could stretch over many months.
When the feedback process gets shortened from months to weeks, it also means the entire innovation cycle at the client end is faster since the inputs needed to make decisions are now available a lot earlier.
Consequently, new product development becomes a lot faster and eventually clients can go to market a lot earlier than before.
More for less
AI can complement HI to give outcomes that are not only more powerful and a lot more agile but also offer much better value for the dollar spent.
Clients can now cover a lot more markets, a lot many categories and have enhanced scope in the same budget.
They can do a lot more for less since AI can save significant man hours that would have been required to be spent via traditional research approaches and programs.
Freedom to iterate
Finally, AI also allows marketers to experiment, iterate, and explore a lot more.
There is no limit to generating ideas, curating concepts, generating pack prototypes, or screening full propositions using AI. Experts in prompt engineering related to these innovation assets can ensure that marketers are spoilt for choice when it comes to articulating and visualizing innovations.
Agencies like Ipsos, can help marketers go-to-market in record time by integrating the power of artificial intelligence with human intelligence accumulated over years of innovation research practice.
By Chirag Madhukar Buch, Senior Research Director, Ipsos, UAE
