Everyone likes a personal note or personal recommendation. And according to marketing research, it works. 78% of consumers say that personally relevant content increases their purchase intent for a brand's products and services.

And it isn’t just marketing chatter. General Mills (Tii:GIS) improved its analytics and, in the process, improved digital sales. On a June 28 quarterly report call with analysts and investors, Chairman and CEO Jeff Harmening said the consumer data effort has helped drive a double-digit rise in digital sales in the U.S.

“We plan to continue to leverage our data and analytical capabilities to assess and improve our presence on the digital shelf,” Harmening said during the call. “These tools and processes enabled us to grow our U.S. eCommerce retail sales by 24% in fiscal ’23, and we plan to continue this momentum in fiscal ’24.”

So where is all this digital data coming from and what are companies doing with it to personalize sales?

According to Fortune Business Insights, the global big data analytics market was valued at $240.56 billion in 2021 and it is forecasted to grow from $271.83 billion in 2022 to $655.53 billion by 2029 at a compound annual growth rate of 13.4% during the forecast period. The increasing data generation from social media platforms like Facebook, Snapchat, WhatsApp, and Instagram leads to significant databases and huge amounts of data that need big data technology for processing.

While some companies crunch the data on their own, others turn to a growing number of companies that do the crunching for them.

Big data, also known as big data analytics, is a term used to describe the massive amount of data that is collected by businesses all the time. It typically describes data sets with sizes beyond the ability of traditional data processing software tools to capture, process and curate in a timely fashion. The data is constantly flowing in from e-commerce, shipping, text messaging, internet transactions, and wholesale and retail transactions.

Big data companies sort reams of data into usable, actionable information. These firms help other companies understand their markets (including any shortcomings), identify customers, spot trends and analyze patterns. The field of data analytics is growing quickly as companies begin to understand how they can use all the information collected daily.

Big data companies are sometimes just that — companies that were founded to dissect, hold or analyze data. They include public companies such as Teradata Corp. (Tii:TDC), MongoDB (Tii:MDB), Palantir Technologies (Tii:PLTR), Splunk (Tii:SPLK), Snowflake (Tii:SNOW), Datadog (Tii:DDOG) and New Relic (Tii:NEWR), to name a few.

Other companies are involved in big data but are better known for the technology they bring to market, such as Salesforce (Tii:CRM), International Business Machines (Tii:IBM) and Dell Technologies (Tii:DELL).

As more data is collected, more help from these big data companies will be needed. Data is worthless if it isn’t analyzed. Big data is becoming more important as a way to provide operational intelligence, enabling companies to investigate, monitor, analyze situations, and then react and respond. Big data is especially helpful for retailers, who can use the information to better understand customers and the most effective ways to keep them engaged. Big data allows them to solve problems faster and make more agile business decisions. In addition, banks use it to help minimize risk and fraud.

As the world and commerce are tied ever closer to the internet and technology, big data is going to continue to pile up. With the right company as a guide, this information can be mined to provide clarity and strategy.