Imagine buying a $20,000 car and then forgetting where you parked it. The car was supposed to take you places, but instead it's sitting somewhere gathering dust, losing value with each passing second. Well, that same thing happens with insights every day in large, global enterprises. And that's why Stravito was founded. In this webinar, Stravito CEO and co-founder Thor Olof Philogène shares how he went from building a global Growth & Analytics team to embarking on a mission to solve the underuse of insights with a user-friendly knowledge management platform. A platform purpose-built for market research and insights that's now used by Electrolux, Comcast, Carlsberg, and other global leaders to leverage more insights. You'll also get to see first-hand how Stravito makes it easy to increase insights ROI by:- Centralizing reports, dashboards, videos, and more- Inspiring stakeholders with relevant, easy-to-digest content- Tailoring knowledge sharing to user needs and preferences
Whether through stakeholder inclusion, contributions to mission & purpose, or improvements in innovation, leading the way for equitable leadership is no small task. In this webinar, Remesh CEO Andrew Konya discussed the impact of equitable leadership in research with industry leaders: Nick Graham from PepsiCo, Mario Carrasco from ThinkNow, and Leslie Willis from Panasonic.
Measure ROI of shelf and off location conversions: a Ferrero case study. It's all about Chocolate!
"I fully trust the predictions of product pre-testing. It is well-invested money!"In a nutshell, that's the change in perception among CEOs which would delight us.Imagine if you could test products before placing them in your sales channels in such a way that you could precisely predict whether the product would be a flop or not. Imagine if you could gather consumer feedback so precisely that you could understand exactly what consumers like and dislike about your product. And finally, imagine that there is a way to evaluate consumer feedback in a scalable and automated way to generate high pre-testing ROI.But how to do that? We found a solution by leveraging the power of semantic analytics and combining it with classic closed-survey questions to a powerful predictive algorithm that enabled us to avoid millions and change our CEOs' perceptions.
Today, consumers are bombarded with marketing communication, making it very difficult for brands to differentiate themselves. Digital-first companies can rely on a variety and richness of datasets which is not always matched by more traditional companies. While market research has traditionally helped brands tease out sharp consumer segments, the same segments cannot always be deployed successfully in media executions. This is a story of how research, data science and media came together to maximise the return on precision marketing investment.
"I fully trust the predictions of product pre-testing. It is well-invested money!"In a nutshell, that's the change in perception among CEOs which would delight us.Imagine if you could test products before placing them in your sales channels in such a way that you could precisely predict whether the product would be a flop or not. Imagine if you could gather consumer feedback so precisely that you could understand exactly what consumers like and dislike about your product. And finally, imagine that there is a way to evaluate consumer feedback in a scalable and automated way to generate high pre-testing ROI.But how to do that? We found a solution by leveraging the power of semantic analytics and combining it with classic closed-survey questions to a powerful predictive algorithm that enabled us to avoid millions and change our CEOs' perceptions.
Today, consumers are bombarded with marketing communication, making it very difficult for brands to differentiate themselves. Digital-first companies can rely on a variety and richness of datasets which is not always matched by more traditional companies. While market research has traditionally helped brands tease out sharp consumer segments, the same segments cannot always be deployed successfully in media executions. This is a story of how research, data science and media came together to maximise the return on precision marketing investment.
During times of economic uncertainty, you might have to slash market research spend. But without data-driven understanding of your customers, it's unlikely that you will continue to be able to address their needs better than your competition. So what can you do to stay competitive and on budget?In this webinar, we'll explain how effective knowledge management can help you make the most of your market research by minimising unnecessary costs and maximising value.
Our journey to better understand the impact of advertising dollars on sales beyond the short run. Operating on a hunch, we ventured to harness the wealth of customer perception data and the best of existing statistical models at Microsoft to deliver measurement of advertising's long-term impact. The value this exercise would deliver to the business, however, was unprecedented.
Up to 85% of brand generated social media posts are wasted. With digital advertising approaching 50% of all advertising expenditure, we need to go beyond clicks and likes as a measure of ROI on social media expenditure. Through machine learning, a brand can now see how many posts support their intended position, how many are off target, and how many are simply ambiguous. This presentation demonstrates how the AI tool works, highlights the role of archetypal alignment across touch points, delivers a practical framework where brands can specifically identify the nature of their optimal social media imagery, and concludes that understanding archetypal codes is the key to optimising ROI in Social Media.
The truth is companies spend millions of dollars on advertising and they don't truly know what works and what doesn't. They have no way to establish a ROI on a TV commercial or a Radio ad. At best, they can estimate the number of people that saw the commercial, but that's still quite far from a return on investment. We were hired by Volkswagen to count the number of people that go into their distributors and ask them a few questions to evaluate the service. We have done this for over a year. Our innovation was to ask Volkswagen for their investment on advertisement day by day. With this data and the data on the number of visits per distributor we develop a model to evaluate which half of the investment was useful and which wasted.