The IT Labs Data Science Think+Do Tank is a 50+ person team comprised of mathematicians, applied physicists, and extraordinary engineers with a dedicated focus on business intelligence, data analytics and data management. Our team has an extensive portfolio in enterprise-grade solutions and services. We can provide complete external services or supplement an internal team.
Unlike traditional business intelligence practices, which are more backward-looking in nature, advanced analytics is focused on helping companies derive actionable intelligence based on past experience by identifying patterns and predicting future behavior.
Predictive analytics for example, can help you understand the purchasing behavior of customers. These insights can drive revenue through smart cross selling and upselling strategies, and create a high return of investments on your loyalty programs.
Today, organizations possess massive amounts of data for combatting fraud. What they lack is the ability to turn all this data into real, actionable intelligence.
We can help your organization effectively leverage untapped data, new data types, and external data sources in order to create intelligent models that will boost your business processes and create completely new revenue streams based on analysis of your client information.
The same massive amounts of data can be used to combat churn, intelligently mitigate risks, target and track your marketing activities with a new approach, as well as other applications we can discover together. Every organization is unique, as is their data landscape, and we are capable of discovering fresh possibilities within your particular environment.
Driver Behavioral Profiling for connected cars. Ability to process and analyze large sets of data received by the connected cars while distributing information for Usage Based Insurance (UBI) and other relevant data.
Behavioral finance – ensuring end user’s risk exposure is in proper correlation with end user risk appetite.
Analysis of specific market segments vs brands (for example students or young adults), listening on social media (including blogs, etc.) to determine key communication topics and decision triggers that influence their choice of which bank to use (or switch to). Supporting targeted marketing campaigns that strive to increase gravitation of chosen segment toward specific bank/brand.
Fraud detection – End user classification algorithms and behavior deviation detection, coupled with key process indicators to flag potential irregularities.
Repositioning support – research the landscape (demographics & competition), gain understanding of targeted end users and their preferences, and develop tactical suggestions to support repositioning a portfolio of products.
End user retention and targeted sales/up-sales discovery, monitoring, analytics and prediction. Understanding end users and providing suggestions on retention and contract renegotiation. Sales team support by calculating probabilities of end user’s positive reaction to campaigns.
End user profiling and analysis with traditional data and social networks in relation to company brands.
Brand key attributes identification, awareness and engagement levels.
Matching market sentiment with personality characteristics of celebrity influencers. Real time re-sellers/end customers/influencers discovery.
Fighting churn on products with low loyalty indexes. Gaining insight on end user roles and behavior by innovative use of social network analysis, thus recognizing the influencers and key players. Focusing marketing on influencers and other key end users that have best overall positive yield to network. Agile refocusing of communication on detection of deviance and “early warning” churn detection. Minimizing the negative effects of churners (that we did not manage to stop from churning) to the overall network.
Brand awareness and penetration to specific market segments, competition analysis and marketing campaign support.
Customer loyalty – using loyalty program data coupled with analysis of social networks, relevant sites (blogs and portals) and introspective brands and products to increase sales, suggest up-sales, understand and use end user purchase seasonality to offer relevant products at the just right moment, create campaigns on special dates and periods.
Suggested campaigns: Valentine’s Day, Christmas, school season, summer vacation, etc., that communicate message with the highest probability of end user’s positive curiosity, coupled with suggestions of appropriate products and bundles that will resonate best with client preferences (and their needs & expected budget/spending positioning).
Significantly reducing inventory by predicting sales on individual shop/city/region basis (based on end users research coupled with machine learning based on understanding previous sales) [need to reword this sentence but I don’t’ understand it]. Minimizing end user churn by ensuring desired products are available on-site, at the proper time and in quantities that are just right.
Upsell prediction and execution with measurable success rate.
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