Data platform vendors and enterprises are attacking the next frontier of analytics – making the most of digital exhaust.

An enormous amount of data currently being generated is not being captured by organizations, even though collecting and analyzing it in real-time is sure to bring about greater efficiency in operations and can help identify trends to develop business in new areas.

The term “digital exhaust” refers to the bits of data that are created every day in the normal course of organizations doing business and consumers using and commenting on their interactions. Information from sources as diverse as legal memos, praise for competitors on Twitter, news accounts, and usage stats on exercise devices can lead to new opportunities to do business or to make business processes better serve existing customers.

At the very least, you’ll be able to provide a more refined customer service experience and predict demand more precisely when you spend more time working with digital exhaust.

More than 44 zettabytes of data of digital exhaust were produced in 2020, experts estimate, according to a recent KUNGFU.AI report, which noted, “To put things in perspective, that is roughly equivalent of 5 billion libraries of Congress or 4 years worth of hi-def video.”

Types of Information Making Up Digital Exhaust

You may not be actively thinking about and working on digital exhaust protocols now, but there are a lot of opportunities to collect this kind of data immediately, just from internal resources.

Examples of digital exhaust that are typically created inside an organization include customer profiles and analytics, logs from call center interactions, service call reports, text messages, email messages, and memos.

You already have easy access to this information. The trick is in storing and then using it, to squeeze meaning out of patterns discovered through analysis aided by machine learning and artificial intelligence.

Examples of digital exhaust sourced externally will include details from web pages, accounts from news reports, government releases, regulatory announcements, consumer credit card transactions, reviews, and social media posts. KUNGFU.AI reported that one company took 30 years of contract data, analyzing losing and winning offers to help them build a system to predict the potential success rate of future offers.

Publicly available information (such as news and reviews) is ripe for you to correlate with your products and services to process the digital exhaust. Other types of information will be in the hands of brokers for you to purchase, such as if you want anonymized information about bank usage or ad clicks.

Internet of Things

Savvy CIOs and CTOs in organizations where the digital exhaust is prime for harvesting know they can use the data to identify and make sense of emerging trends and come up with new solutions or improvements to products they market to consumers or other businesses.

A particularly rich source of information is coming from the Internet of Things or IoT devices. They range from smart home devices that people speak to when ordering deliveries or looking up something on the internet, to smart thermostats, to sensors inside factories that communicate real-time data to other automated equipment to ride herd on manufacturing processes.

Wharton University explored how organizations are using digital exhaust to their competitive advantage. For example, a startup company called Propeller Health embedded a sensor in inhalers people use for treating COPD and asthma, to collect data in real-time.

The company analyzed the trove of data collected from patient population usage patterns, correlating it with external sources of data including air quality index and weather reports. This information went into providing personalized coaching to patients in real-time, resulting in a 50% reduction in unplanned asthma attacks among its customers.

Another case in successfully harvesting digital exhaust data came from farming equipment made by John Deere. The company launched an initiative to gather more data from fields, tractors, and other equipment, jumping from 190,000 data points each day in 2014, to as much as 4.1 million points in 2020. “By turning these data streams into insights and prescriptive analytics, or automated decisions based on data, Deere moved from selling farm equipment to delivering ‘Precision Farming’ services, guided by their data advantage.

Data from Point of Sales

Corporations tend to generate three main types of data useful for gathering in digital exhaust efforts: transaction data (such as from customer sales), corporate data (such as internal memos and contracts), and government agency data that organizations must stay on top of to remain in compliance and to follow industry best practices.

A major source of valuable information comes from supermarket scanner data, which can be correlated with all types of other data points to make it more valuable and to provide insights previously unattainable, such as how weather patterns influence sales of different products.

“It is widely believed that aggregated credit card transaction data offers the most reliable indicator that provides insights on price formation, inflationary expectations, and product-level profitability, reported Towards Data Science, which noted that this data can “act as a leading indicator of revenues as well as determinants of profitability.”

Email messages are another useful source for digital exhaust. For example, camera manufacturer GoPro’s shares tumbled in November 2016 after analytics revealed that sales volume went down at the product’s point of sale, based on information sourced from product receipts in 3 million email boxes.

Sales Development via Digital Exhaust Data

From shoes on the street to suits in the boardroom, there are many opportunities for gathering data to then influence the sales process.

Nike is now using sensors for digital exhaust collection, per Wharton, allowing it to gather precise information on the behavior of 7 million users, including how far they run each session to predict when the treads are about to wear out, which is data then used to boost sales.

An example of enterprise efforts to increase sales can be seen with Microsoft, which purchased a company called VoloMetrix. It made a tool that scrapes an organization’s email and calendar metadata to better map out and analyze how workers allocate time, augmented with survey responses.

As Harvard Business Review put it, “The software shows how the sales capacity is being deployed across different customer segments, so managers can see whether their sales organizations are truly focused on high-priority customers.”

Another VoloMetrix data set showed that sales reps at a B2B company were spending less than 30% of their time interacting with customers, with most of the workday spent in company meetings or engaging with non-customer-related emails and tasks. Armed with this insight from digital exhaust, managers at the company determined they had excess sales force, so they reduced salespeople, cutting costs.

Determining What Sources of Digital Exhaust Will Benefit Your Organization the Most

Every organization will have a unique approach to harnessing digital exhaust, simply because of the variety of sources and the degree of appropriateness for each particular channel of data. Your organization might focus on working with real-time data from external sources such as web pages, social media, credit card transactions, ad clicks, news reports, and social media messages.

Or, you find it’s most suitable to pay attention to previously unexplored internal data, such as memos, service reports, contracts, customer service communications, and patterns discovered by poring through years of email messages and voicemail transcripts.

And chances are that some of the information your organization will be counting on using will originate from IoT devices, which you may sell to customers yourself, or purchase from data brokers.

With so much data coming in these categories, you’ll need to adapt your processes, using artificial intelligence to help sift through the data and turn it into action that can boost your bottom line and help you gain more market share.