Competitive Intelligence & Product Intelligence
According to research from BCG and Google, Consumer Packaged Goods (CPG) companies that adopt Advanced Analytics (AA) and AI technologies at scale can boost revenue by over 10%.
Imagine Nike, and it’s $40B in revenue growing by 10-15%!
Competitive Intelligence is part of the AA family that helps brands understand what is going on in their market. The more refined the Intelligence is, the better, and the best is Product Intelligence, which can reflect to brands their product strengths and weaknesses and their competitors.
Mastering competitive Intelligence becomes critical in an era where the products sell themselves online. This article will cover the need for Product Intelligence and explain how Revuze uses unique AI technology to uncover it.
Product Intelligence level Competitive Intelligence will grow your revenue as it offers answers to several key challenges:
- The need for quality feedback for the eCommerce/D2C channel
- The need for personalization data in a world where personal data becomes limited
- Early warning system for new brands/products
- Innovation ideation source for new products or product evolution
For example, knowing that there is a mismatch between your product page online and what consumers expect is vital to improving consumer satisfaction and star rating. Similarly, knowing the drivers for star rating online for a key product or a competitor product can help you understand what needs to be done to get a higher star rating for your products.
With online sales (eCommerce and D2C) booming to over 20% of US retail sales, communications with consumers become more digital.
This is timely as technology is now available to be able to capture and analyze this public communication taking place via reviews, Q&A, forums, etc.
Imagine being able to analyze 30% of all the verified buyers within an industry…this is unparalleled in market research terms.
How Revuze uses AI to generate Product level Competitive Intelligence
The key challenge with AI today is training it. AI is great in repeating a task once it understands it, and that understanding phase today requires experts – data scientists and analysts, to “explain” it to the AI software.
Revuze invented the AI machine that can train itself, eliminating the need for experts. With this is delivering a functional revolution:
- Highly granular insights, as machine training, are much broader/deeper compared to human-based training.
- Immediate, direct access to insights. No need for mediators (experts, IT…) to help customize results.
- The simplicity of access, delivering insights to any business role within brands
Our AI works similarly to how humans work, only faster and without getting tired or sidetracked, and in the process, it handles all the mundane tasks that assure the data analyzed is of high quality and cleanliness. It is essentially working like any human industry expert – it is reading all the opinions possible about an industry from different data sources and is self-training to become an expert on that specific industry. The only difference between humans is the capacity/scalability. Our AI can become an expert on the industry in a matter of hours and can repeat the same for any number of industries.
On a per industry level, these are the typical stages our AI goes through when processing data:
- Public data is collected from multiple online sources. Brands can upload internally collected opinion data.
- Data is aligned between the different sources.
- Data is cleaned for relevancy, duplicated opinions, etc.
- Sub hierarchies in the industry organize data (For example male/females Shampoos in the Shampoo industry).
- Topics are discovered per industry.
- The sentiment is discovered per sentence per industry.
- Topics and sentiments are associated with each sentence, SKU/product, brand to provide an industry view.
- The entire process repeats itself on predefined update points – so brands can gain an ongoing sense of trends and changes in the industry regularly, for example, every week.
With public reviews and opinions, this approach allows brands to gain an industry-wide understanding of competitors, new products, new brands, and trends. This is also done at a very different scale compared to traditional intelligence methods as online opinions in an industry can easily scale to hundreds of thousands of opinions if not millions.
As eCommerce/D2C becomes a major retail channel, it also turns online commerce into a key communication and feedback channel for brands. As more public consumer opinions become available online, the more information you have from verified buyers. This is a great opportunity to gain industry intelligence from millions of consumers in a market, and in the process, get to know all that is going on in your industry – new trends, new brands, wish lists, change of tastes etc. This is great for multiple stakeholders within brands who can now make data-driven decisions in near real-time:
- Product evolution/innovation.
- Marketing strategy.
- eCommerce optimization.
- Customer service.
Simone Somekh is a New York-based writer and editor who specializes in marketing and communications for B2B SaaS companies. He teaches Communications at Touro College and he is the author of an award-winning novel published in four languages.