In this series of blogs, Daniel Pitchford investigates the ways AI investments can help successfully scale up a business.
There are many ways of thinking about AI innovation around product output, and it’s important to recognise the increasing ubiquity of this technology in our daily lives. Take the presence of Office 365 in our workdays: it has an estimated 1.2bn users worldwide and is often the go-to for UK businesses of all sizes. Even the royal family held its recent crisis talks over Skype for Business.
However, the final post in my AI for scale-up series focuses on the main ways in which companies can benefit from applying AI throughout a product’s lifecycle – from coming up with new product ideas to integrating AI into existing offerings and on to the marketing and targeting processes. In the rush to automate, leaders often overlook the potential of how smart uses of AI can transform their own products in the scale-up process.
(A)I see what we can do next
Deliveroo, the food delivery company, provides an excellent illustration of how artificial intelligence can help develop new products and enhance an existing offering. In 2018, the company realised that it could use its years of data looking at takeaway ordering habits to reduce costs in the kitchen. Enter its dark kitchens: industrial delivery-only spaces that white label popular restaurant brands. Gone are the front of house and maintenance costs, now suppliers and cleaning resources can be pooled, data can be crunched to predict when to have lots of katsu curry ingredients available versus pizza dough, and in 2020 we are seeing more of its Deliveroo Editions (the branded name for its dark kitchens) open.
The lesson here for other scale-ups is to consider how AI can help streamline, diversify and evolve your offering. Deliveroo knew the UK takeaway industry was booming at a massive rate – 14 percent year on year – and it wanted a bigger slice of profits. Its revolutionary move created a sea change in the industry.
Launching and maximising marketing efforts
AI can also help with launching and marketing products, from launch strategies to key product development (KPD). Spotify crunched its numbers and realised listeners using its smart “Discover Weekly” playlists spend twice as much time on the app than people who don’t. It used this AI-driven insight (for its AI-driven hyper-tailored weekly playlists) to launch new brand partnerships. The first was with tech giant Microsoft, who had access to the music service’s 109million users who use the free service (with adverts) for an ad campaign discussing the impact of AI on the modern world, from healthcare to learning.
The Sponsored Playlist ad product is now available for other collaborations – including Spotify’s support developing marketing plans to best reach and impact its audience.
When it comes to advertising, carmaker Lexus showed it’s possible for AI to generate an entire script: it used IBM’s Watson technology, 15 years of award-winning adverts and data-feeds related to decision-making to create the world’s first fully AI-automated advert. Marketing technology start-up Visual Voice applied Watson AI to develop the non-human element and bring to life the intelligence of the technology driving the car’s safety and security features.
Another excellent use of AI in product launch is to inform KPD and knowing both when and how to pivot or drop dying product lines. ASOS, the ecommerce giant, recently shared details of its internal hackathon, where its retail and AI teams collaborated to help innovate. The result was a way to understand “hero” products and ensure they’re not lost amongst the 5,000 new products added every week. While ASOS transitioned away from being a true ‘scale-up’ many years ago, businesses of all sizes can benefit from this hyper-critical whilst constructive internal approach.
Using AI to reach the most relevant people
If you’re finding it difficult to reach people, it’s possible to use AI to ensure product descriptions match what people are searching for – Alibaba’s marketing arm Alimama’s copywriting AI is made available to ecommerce merchants. The Chinese tech giant isn’t the only company offering this service: there are plenty of ecommerce packages available to ensure platforms don’t haemorrhage customers with poor descriptions. They can scour the web to look at the way products are talked about and use this to build the most relevant, searchable and accurate description possible.
This application of the technology doesn’t end with product descriptions: it can be used for content writing, SEO development, and hyper-tailored marketing. Put simply, there are highly complex algorithms guiding what’s being pushed to you. Take Alli AI, which works with the likes of New York Times and Expedia to provide smart SEO support. It uses the technology to take over manual (and often frustrating) functions like adjusting campaign variables to boost rankings – and crucially, automatically update when search engine algorithms change.
Elsewhere, PAVEAI turns Google Analytics data into workable insights for small-to-medium businesses and ecommerce sites. For example, “On May 17th 2019, your white t-shirt sold 50% more than usual – consider promoting this again in May 2020.” A scale-up can easily harness these smart technologies as add-on packages – and in doing so, reap the benefits of the AI analytics and recommendations to reach people.
Ultimately, AI can ensure the right people are aware of your product. Whether that’s using the technology to see gaps in the market, such as Deliveroo with their dark kitchens, or harnessing the creative applications in script writing like Lexus, or, like ASOS, using it to ensure hero products are maximised to their full potential – there are many reasons why AI should be part of your product lifecycle if you’re striving for scale.