Uniting Business Strategy through Analytics

Perhaps one of the most challenging areas of business is ensuring that everything within the enterprise is well-synchronized. It sounds a lot easier than it is: corporate image and branding has to be aligned with message; message has to be aligned with product design; product design has to be aligned with performance, which has to be aligned with production issues; production with raw material procurement…and so on.

But where and how does the enterprise begin to pull all these threads together? How does it know what is going to drive its product development strategies; its sales and marketing strategies; distribution plans; achieving financial objectives?

There is one over-arching requirement to ensure that everything gels as it should…and that is the need for deep, clear and understandable analytics.

Not just “what” the market is doing; not even just why it is behaving in a specific way, but a set of well-defined analytics that deliver the full story of market and consumer/customer/micro and macro environmental behavior.

For example, traditional marketing takes a wide net approach to outreach, casting broadly with generic promises in unsegmented markets. But with big data available to modern businesses, savvy marketers can now create personalized, predictive outreach initiatives by demystifying marketing ROI and translating analytics into profitable action.

With Strategic Marketing Analytics enterprises are able identify which types of Big Data are most relevant to the business and learn how to locate and interpret them to make more valuable marketing investments, deciphering big data to boost sales.

There are many possible applications for Big Data in business, including customer segmentation by profitability. The examination of data-driven feedback, allows companies to respond to crises in real time and avoid market failure. Analyzing Big Data will enable enterprises to track the effectiveness of current campaigns on sales, profits, customer acquisition, retention, and referral rates.

In this digital age, retailers’ digital and business strategies are unifying as consumers increasingly expect a more customized shopping experience — one that provides value and convenience. Their expectations are higher than ever before, with more choices in products and more ways in which to interact with retailers. This is a huge challenge in an industry already dealing with complex operations and intense competition.

Analytics have enabled online retailers to provide shoppers with customized offers based on their likes, dislikes, past purchases and browsing histories.

When consumers visit a website, they leave behind a data trail. This data, combined with customers’ purchase and social data, allows an online retailer to provide customized product recommendations or discounts and special offers. Analytics on in-store shopper behavior help retailers know more about their shoppers’ in-store journey. This allows them to provide a better, more personalized in-store experience, much like an online shopping experience. By giving customers what they want – value and convenience – retailers can gain a competitive advantage by differentiating their brands.

Strategies for different departments and functions within the enterprise can be unified through the analytics thrown up by the data.

A common goal can be far more easily seen and understood, and a more targeted approach can be developed.

It should be easy to collect and store data, while giving enterprises the powerful tools needed to analyze it. Tracking user behavior across all channels and aggregating the data to help capitalize on invaluable insights, empowers companies to stay totally up to date with all data tracked from basic clicks and site engagement to downloads, video plays, advertising, social network activity, and sales results.

A business manager needs context for analysis: unifying data from a multitude of external and internal sources, and inspecting all of the data as one unit, all the various facets of user and customer behavior in the context needed to provide comprehensive business insights can be understood.

This will enable Behavioral Analytics –a game-changer which provides deep insights into customer behavior. If regular business analytics is about the “who”, “what”, “where” and “when”, behavioral analytics focuses on the “why” and “how”. Behavioral analytics allows the use of seemingly unrelated data points to identify errors and predict future trends in the way users behave within eCommerce, gaming and web applications.

Behavioral Analytics look beyond data alone to search for patterns and groupings of individual actions, as a time-based sequence of user behavior, which leads to actionable change and improvement. This could be the key to answering most business questions.

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