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Business teams constantly want to know how their companies are performing — against their internal goals and those of the market they compete in. They benchmark their performance against their previous results, what their customers are asking for, what their customers are buying, and ideally what their customers will buy. To get their answers, businesses typically rely on data sources that are all internal, showing decision-makers only part of the picture.
That’s now in the past. Today, through a strategic partnership, Signals Analytics and Sisense are making it easy to incorporate external data analytics into a company’s main BI environment. The result is a broader, more holistic view of the market coupled with more actionable and granular insights. Infusing these analytics everywhere, democratizes data usage and access to critical insights across the enterprise.
Organizations who are truly data-driven know how to leverage a wide range of internal and external data sources in their decision-making. The integration of Signals Analytics in the Sisense business intelligence environment gets them there faster and seamlessly, without the need for specialized resources to build complex systems.Kobi Gershoni, Signals Analytics co-founder and chief research officer
Why external data analytics?
The integration of Signals Analytics with the Sisense platform delivers on the promise of advanced analytics — infusing intelligence at the right place and the right time, upleveling standard decisions to strategic decisions, and speeding the time to deployment. Combining internal and external data unlocks powerful insights that can drive innovation, product development, marketing, partnerships, acquisitions, and more.
Primary use cases for external data analytics
External data is uniquely well-suited to inform decision points across the product life cycle, from identifying unmet needs to predicting sales for specific attributes, positioning against the competition, measuring outcomes, and more. By incorporating a wide range of external data sources that are connected and contextualized, users benefit from a more holistic picture of the market.
For example, when combining product reviews, product listings, social media, blogs, forums, news sites, and more with sales data, the accuracy rate for predictive analytics jumps from 36% to over 70%. Similar results are seen when going from social listening alone to using a fully connected and contextualized external data set to generate predictions.
The Sisense and Signals Analytics partnership: What you need to know
- Signals Analytics provides the connected and contextualized datasets for specific fast-moving consumer goods (FMCG) categories
- Sisense users can tap into one of the broadest external datasets available and unleash the power of this connected data in their Sisense dashboards
- The ROI of the analytics investment dramatically increases when combining historical data, sales, inventory, and customer data with Signals Analytics data
Integrate external data analytics in your Sisense environment in three easy steps
Step 1: Connect
From your Sisense UI, use the Snowflake data connector to connect to the Signals Analytics Data Mart. The data can be queried live in the Sisense ElastiCube.
Step 2: Select
Once the data connection has been established, select the data types needed by filtering the relevant “Catalog.”
Step 3: Visualize
Select the dimensions, measures, and filters to apply, then visualize.
More data sources, better decisions
Your company is sitting on a large supply of data, but unless and until you find the right datasets to complement it, the questions you can answer and the insights you can harness from it will be limited. Whatever your company does and whatever questions you are trying to answer, mashing up data from a variety of sources, inside the right platform, is vital to surfacing game-changing insights.