How Consumer Analytics Can Grow Your Business
Big data is big business, and it’s become an increasingly vital tool for companies to connect with the right consumer at the right time. It’s also a constantly evolving concept because each new technological innovation provides a new opportunity to gather, scrutinize, and interpret data. Businesses that know how to harness data’s potential can develop smart, efficient strategies that can lead to robust growth.
To learn more about big data and consumer analytics, check out the infographic below, created by Maryville University’s online Bachelor of Science in Marketing program.
The Rise of Consumer Analytics, by the Numbers
A wealth of data is out there, coming from a wide variety of sources. Organizations that know how to harness the power of analytics can reap benefits that can help their businesses grow.
In 2021, an estimated 2.5 quintillion bytes of data were created every day. Experts predict that number will grow over time, and by 2025, nearly 200 zettabytes of global data storage will be needed. Furthermore, experts project 100 zettabytes of cloud-stored data will be generated by 2025. So where is all this data coming from?
Collectively, search engines are one of the biggest data generators. This is due to frequency of use. Google, for instance, saw 8.5 billion searches every day as of early 2022. This number translates to 99,000 searches per second.
Social media is also a key primary source, gathering data from various user actions or activities. In 2021, on a per-minute basis, Instagram users posted 65,000 user photos, Facebook users shared 240,000 photos, Facebook Live received 44 million views, and Twitter users posted 575,000 tweets.
Data also comes from online entertainment platforms: Netflix generated 452,000 hours of streaming every minute in 2021, while YouTube users streamed 694,000 hours’ worth of video content per minute. Apps are yet another source: TikTok users, for instance, watched 167,000 hours’ worth of videos per minute.
Finally, business operations produce plenty of usable data. On a per-minute basis in 2021, 100,000 users connected to Microsoft Teams, 12 million messages connected to iMessage, 148,000 messages were sent on Slack, 856 minutes of Zoom webinars occurred, and 208 rooms were created on Clubhouse.
Economic Impact of Data
Data attracts attention in marketing due to customer analytics, which are the data processes and technologies that give businesses insights into consumer behaviors. Understanding these insights allows businesses to provide offers based on metrics like anticipation, relevance, and timeliness.
The customer analytics market is projected to grow from $5.24 billion in 2020 to $20.82 billion by 2028 — a growth of 19.3%. There are several reasons for this changing landscape, including partnerships, collaborations, and agreements; mergers and acquisitions; and product launches and product expansion.
Using analytics in business can carry several benefits, including increased profitability, better decision-making, clearer market insights, and improved efficiency. There are also several customer-related benefits to data analytics, such as improved customer experience, identified consumer trends, and stronger customer relationships.
Reaching the Right Consumer
When data is used properly, it can help a business reach the right customer with the right product at the right time. The path to this customer comes from properly mining information from numerous sources.
Organizations can use a range of methods, from traditional means to tech-driven ones, to collect data. Traditional methods include direct and indirect interviews, questionnaires, and focus groups. Tech-driven methods include automated data, webpages, and social media.
The types of data collected by these traditional and modern methods focus on personal, engagement, behavioral, and attitudinal consumer information. These avenues can allow a business to glean a more holistic insight into the consumer.
Building a Solid Data Analysis Strategy
Data can yield powerful insights into consumer behaviors and desires. But without a solid strategy in place, data is just random bits of information. Businesses can ensure the building of these strategies by bringing data scientists into the fold.
Types of Analytics
There are three basic types of analytics — descriptive, predictive, and prescriptive. Each type can produce different consumer insights. Professionals in data science roles can use these data types to carry out their essential tasks, which include developing data analysis strategies, preparing data for analysis, analyzing the data, interpreting and visualizing the results, and building data-driven models that demonstrate the results.
Several well-paying career paths fall under the data science umbrella. Data analysts, for instance, earn a median annual salary of approximately $62,500. Data engineers earn a median annual salary of about $93,000, and data scientists earn a median annual salary of about $97,000.
Building a Better Business with Consumer Data
Everyone wins when a business uses data analytics to gain customer insights and reach the right people. Customers are happier and businesses are more profitable. By deploying their knowledge and skills to help turn data into actionable strategies, data science professionals can be a key part of this successful formula.