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JARGON BUSTERS

What is NLP?

Natural Language Processing (NLP) put most simply is the field of using computers to understand and analyse human language (inclusive of sarcasm, colloquialisms, emojis etc.) to gain an accurate depiction of its content and sentiment. It means we can read and make sense of millions of pieces of consumer generated digital content within a matter of seconds.

What is TPV?

TPV is a scientific ranking metric that helps brands identify which trends to prioritise for action. It assigns a comparative value to each of the thousands of trends within a category, enabling trends to be ranked objectively based on their predicted importance in +6 months’ time.

What is Machine Learning?

A subset of AI that includes statistical techniques that enable machines to improve at tasks with experience. We use Machine Learning to solve complex problems where defining the rules of what the solution has to DO is impossible. Instead of programming rules we teach the machine via examples, so we define what we EXPECT from it and the machine learns the rules. For instance, giving precise and robust rules why a Social media post is positive/negative/neutral is impossible. Instead, we manually label several thousand posts then make the machine learn the rules based on this training dataset.

What is AI?

Artificial Intelligence (AI) is a broad term for techniques that enable machines or programmes to perform what are deemed as ‘intelligent tasks’ otherwise performed by a human with much greater capacity and speed. We use forms of AI, namely NLP and Machine Learning, to turn unstructured Social data into meaningful business intelligence.
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We’ll be in touch soon. Until then, here’s some reading to whet your appetite.

Many large CPG firms are struggling to innovate fast enough, and this is leading some to experiment with different business models and different ways to get things through their large systems. The cry of ‘be Agile!’ can be heard in many corporate offices, and with this push to be more agile it could be easy to think that stage gate processes should be abolished altogether.      However, before your team goes rushing to burn down the halls of the stage gate process, let’s take a step back and discuss why it was set up in the first place – and following that – how you can make it faster, leaner, and more predictive – without entirely abandoning the positive things a stage gate process provides.   Why have a stage gate process in the first place?   The goal of any stage gate process is to increase the ROI (Return on Investment) from the company’s spend on Innovation and New Product Development.   How do you achieve higher ROI? In my role at PepsiCo where I helped define and standardise the research steps within the stage gate process, there was a function called ‘Commercialisation’.  Led by Garry Clancy, one of the primary responsibilities of this function was to manage and run the stage gate process – of which research is just one input. Garry had a simple way to explain how we increase innovation ROI: “Do the right projects, and do the projects right” Garry Clancy, Senior Vice President, Global Innovation & Commercialisation, PepsiCo   So what does that practically mean, and why is it important?  If you are a small company and you only launch one or two innovations a year, then you don’t really need a stage gate process.  Setting up an agile team and having regular check-ins with stakeholders will enable you to have the right level of input to avoid risks and optimise your ideas. You can still use the research tools I will describe below to improve your ROI, but you won’t need a stage gate process with the same level of formality and oversight as a larger organisation.   However, if your company is launching multiple innovations each year – potentially across different divisions or regions, then it becomes more important to have a standardised system for evaluating innovation and comparing innovations against each other.  Decisions need to be made to prioritise resources and ensure that the right ideas are being worked on (those with the highest chance of a strong ROI), and that those ideas are as good as they […]

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Since the beginning of market research in the early 1900’s, companies have been trying to understand the needs of their customers, find ways of improving their products, and validate new ideas before spending large amounts of money developing them.

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As briefs go, it’s not often you get asked by a leading platform to explore what makes their content, and how people engage with it, unique. Yet, this is the challenge Pinterest and other content platforms face to keep Advertisers engaged and to differentiate themselves in an industry where ‘trends’ are the commodity.

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Non-Alcoholic Beverages Predictions Report

In a fast-changing marketplace, how do you understand the future growth opportunities of your category?

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