How Universal Avenue increased earnings for their B2B sales team by creating advanced predictions based on internal and external data streams.
Shopping Discovery at the local level - local businesses learn from their customers and other businesses around them to grow their business in the age of mobile. In a segmentation study conducted among consumers and small business across eight countries, Facebook and their research partners FactWorks looked into local shopping habits and the need for a mobile friendly digital presence, integrating survey data together with Facebook internal data to maximise insights. Results were used to create two standalone segmentations for consumers and local business and typing tool offers opportunities to scale the research into other market. The goal is to deliver a fundamental understanding how local business and consumers interact with each other and how local shopping has changed and is evolving trough digital channels and mobile.
Automation and neuro-research are the two biggest waves in consumer research market ocean. In the nearest future, they will revolutionise the entire industry by merging into one huge tsunami- automated neuro-research- a process understandable and accessible to everyone. Can you image this?
Tackle the most common challenge when developing data-driven solutions: How to define a tangible use case? The Supercrunchers will walk you through based on a real-life case.
The future of the television begins and ends with measurement. This paper will go through the challenges and opportunities with programmatic TV and the new data sources that fuel the programmatic opportunity. Beatgrid's has a single-source approach to measure Tv & video advertising exposure across screen and platform, at the respondent level. It is now a long-awaited reality to better understand incremental Reach & Frequency across platform and to understand creative effectiveness, campaign efficiency and effectiveness, by platform.
Borrowing techniques from record linkage and using the latest algorithms from machine learning to link survey data with internal data, whilst still maintaining the individual anonymity.
This paper will talk about my learnings and give simple solutions to several analytical and technical challenges faced by most mid-sided companies working in the insights and strategy sphere- companies that don't have the kind of large-scale IT infrastructure support often taken for granted in big technology companies. A product-based tech company typically solves a single problem by making one specific product while every project we do is different, with new questions every single time requiring tailored solutions.
Segmentation is a daunting task for the researchers regardless of the category. in Saas 'Freemium' business, adopting a layered approach for integrating multiple sources of data into segmentation is challenging but well worth the effort. Triangulating the primary and secondary sources of data requires subtle alchemy- the magical process of transformation, when everything starts making sense. Users' needs, feature requirements, engagement level, revenue implications, their motivations and aspirations everything come together and bring the segments to life.
Snapchat, Instagram, Pokemon Go, Uber and Venmo are just few of the app brand launches of the past five years that have gobe on to become household names. Using the wide range of connected data at its disposal, YouGov set out to understand the most significant factors driving adoption of successful mobile apps in the US, and identify the apps with the highest propensity to take off in 2018. We belive that the apps with the greatest likelihood to "fly" in 2018 are Moviepass, Wish, and NewsRepublic. This paper outlines the research methods, rationale and insights that led to this conclusion.