This week on the blog, we are focusing on how organizations leverage configurable data platforms like Skai to increase the impact that analytics has in driving optimal business decisions. We will spotlight how different stakeholders interact with the platform, as it gets deployed across an enterprise organization to support various departmental needs and business objectives.
Yesterday’s spotlight focused on how data and analytics teams use Skai – to leverage its connected data set, accurate data classification technologies and taxonomies, and to enrich the business intelligence environments they are responsible for building and maintaining.
Today’s Spotlight: Consumer & Market Insights
Market research and business decisioning is more important now than ever before. From better understanding consumer motivations for the short and long term, to navigating shifts in brand loyalty, purchasing channels, and specific needs brought out by the pandemic, consumer and market insights (CMI) teams are sitting in the driver seat in getting organizations to be data-driven when it comes to keeping their organizations focused on the customer and where future growth will come from.
Skai helps consumer and marketing insights teams succeed by providing several key capabilities through its advanced analytics platform:
Ecosystem trend analysis – From COVID-19 to Black Lives Matter, the recession, Direct to Consumer and overarching industry trends, product development and innovation today is impacted by factors that go way beyond a specific category. However, obtaining a detailed grasp of the dynamics and interactions between different category segments and other macro trends is extremely difficult for consumer and market insights teams to get to, given most of the market intelligence is embedded in external, online sources which are unstructured and vast.
Skai Market Overview apps do the heavy lifting, connecting more than 13,000 data sources and presenting a multi-dimensional view of the product category. The insights are presented in an actionable manner, helping Decision Sciences teams as well as CMI, as they look for insights that relate to specific business questions.
Highly accurate predictive analytics – Most predictive analytics approaches rely only historical sales data, but the addition of other data sources makes the outcome more rich, specific and highly accurate. For example, internal Skai studies show that applying sales data alone to a predictive model can yield about 36% accuracy, while enriching it with other sources can double the results. At the same time, predictions are not static and market conditions change, so having a platform that can yield timely insights is critical for CMI teams who must have a constant feedback loop to the business organizations they serve.
Creating a single source of truth – With constantly changing business priorities and internal and external data sets that are also continually updated, CMI teams are under significant pressure to keep up. With a connected data set bringing together more than 13,000 data sources and the ability to ingest any internal or other third-party source (i.e., Nielsen, IRI, Brandwatch, Profitero, etc.) at scale, Skai establishes a single source of truth for an organization, contextualizing different data sets with configurable taxonomies that makes for actionable and meaningful insights that a CMI team can deliver on.
————————————–
*This blog post originally appeared on Signals-Analytics.com. Skai acquired Signals-Analytics in December 2020. Read the press release.
More like this
powered by Borlabs Cookie