How Small Businesses Can Leverage Big Data for Growth
BY: MATT SHEALY ON MONDAY, JANUARY 14, 2019
Businesses of any size, but especially smaller businesses, are always looking for any edge or means to drive sales and induce growth.
One of the ways in which a smaller business can level the playing field is through data analysis, particularly larger pools of data that might reveal broad customer trends. The pools that represent significant sections of a customer base are collectively known as big data.
This article will give you an overview of big data and discuss the various ways in which small businesses can utilize and ultimately leverage big data to grow.
What is Big Data?
The term “big data” can apply to any number of industries or sectors, and the term itself is nebulous. Big data for some businesses could constitute dozens of customers, while big data for other businesses could mean thousands or more.
As the name suggests, big data is a simply a collection of information that cuts across large segments of the population. A primary goal of data analysis in business is to derive insight into a given customer or client base in order to make smarter decisions and implement business strategies more effectively.
Another goal of collecting and sorting through big data is to identify trends within a given market, and then to exploit market inefficiencies or otherwise use the data to leverage the market and manage budgets more responsibly. This concept is doubly important for small-business owners.
Big data can be structured or unstructured, meaning that some data can easily be categorized while other data fails to fit predetermined categories. Data that defies categorization is much more prevalent, and data analysts need to be cognizant of data that may not fit predefined categories as they sift through various data pools.
Both structured and unstructured data can be extremely instructive in helping analysts understand business and spending trends, and both forms of data have merit. Analysts for small businesses might find greater opportunity in various forms of unstructured data, as this type of data is more likely to be overlooked in many cases.
In short, data can be sorted in any number of different ways, and data pools can vary greatly in size. But the defining aspect of big data is that it accounts for a large percentage of given customer or client base, whether those figures are in the dozens, hundreds, thousands, or even millions.
Why is Big Data Important?
In most cases, the size of a data pool is not nearly as important as what a business chooses to do with the available data. But the benefit of big data is that it provides a larger sample size and could help businesses that need to be conservative with their spending – namely small businesses – make more precise marketing, production, and advertising decisions.
Careful data analysis can reduce costs in both time and money, push businesses toward smarter and better product development, and in general improve budget allocation. All these factors ultimately contribute to a business’s growth.
The combination of big data with sound analytics can also help accomplish the following tasks:
- Creating coupons that align with current customer spending habits
- Determining a core customer base
- Finding flaws in a marketing or advertising strategy in a timely manner
- Reducing risk while optimizing expenditures
As you can see, any business can benefit from good data analysis, and a bigger data pool allows for more accurate, thorough analysis.
Who Can Benefit Most from Big Data Analysis?
Any business can benefit from good data analysis. But small businesses, in particular, can make effective use of big data analysis in a myriad of ways, all of which can contribute to growth and prosperity.
The people who tend to benefit most from data analysis are those responsible for marketing a given business. Marketers need to be shrewder than ever, carefully gauging how clients or customers are reacting to given promotions or advertising campaigns.
The goal of any marketer is to generate more revenue for their client or company via sales, and continuously monitoring the spending trends of customers can help marketers learn how to optimize a customer’s experience with a given company or product.
Smaller businesses can really benefit from careful data analysis, as analysis through multiple filters and perspectives can help small business marketers learn more about their primary customers. This leads to smarter spending on advertising and promotional materials.
Because both the advertising and production budgets of small businesses are comparatively limited, smart data analysis can also help a small business find its niche with a given market by identifying the core customer or client base.
Finding a market niche is a huge benefit to a business working with a finite operating budget. Small businesses can then allocate advertising and marketing dollars more effectively once they understand which customers are driving the bulk of their sales.
The Relationship Between Big Data and Small Businesses
As anyone who operates a small business will tell you, businesses without heavy corporate backing need to identify and utilize different types of market opportunities than those with greater financial support.
In general, a small business needs to operate smarter than a bigger business since small businesses tend to have much less margin for error. A poorly planned advertising campaign can cripple a smaller business, while bigger businesses can often throw ideas at the wall until something sticks.
One of the main ways in which a small business can thrive in an ever-expanding market is to identify potential consumers or customers that might not be obvious to a bigger business. This is a key example of locating a market anomaly.
For instance, big data analysis could reveal that 60% of a given business’s customers are females between the ages of 50-65. This information could (and should) greatly dictate the way in which the business or service is marketed or promoted.
Other Ways in Which Big Data Can Grow a Small Business
The ways in which data analysis can help improve the bottom line of a small business are only limited by the creativity of the marketing team, as well as the ability of an analyst to interpret the data.
Below are some specific ways in which big data can be effectively used to leverage a market, and ultimately help grow a business:
1. Analyze Trends Before Acting
Small businesses are now able to use big data to help plot the course of their chosen venture. Because big data provides so many different insights into the behaviors and purchasing habits of customers, small businesses can gain better insight into the direction of their industry overall.
This foresight can lead to innovation, and a small business can begin developing the next product or service that their customer will want rather than chasing the game all the time.
This not only improves the profile of a small business, but also engenders the type of customer loyalty needed for sustained growth.
Advanced big data reports can help small businesses predict the future of their respective industries, allowing owners to chart a smarter course, innovate, reduce customer turnover, and minimize poor spending decisions.
2. Data Itself Is Not Expensive
The California Polytechnic Institute did a study on the cost effectiveness of big data in 2015, and their conclusions wouldn’t surprise most people. Data analysis ceases to be cost-effective when larger consulting firms are hired to interpret that data, as the fees these firms incur largely offset the benefits of the analysis.
However, data itself is not particularly expensive, and in many cases, economic and sales statistics can be obtained for free.
A way in which a small business can leverage a market is by obtaining and interpreting their own data. While this requires a degree of skill and understanding, a small business owner might be able to derive unique insights from their own data analysis, without incurring the costs associated with hiring a consulting firm.
3. Gauging Price Sensitivity
An under-considered aspect of any good or service is likely its price sensitivity, meaning the figures at which sales ebb and flow.
Some goods are relatively unaffected by price fluctuations. For example, while drivers certainly prefer lower gasoline costs, the price-per-gallon does not have a drastic impact on most peoples’ decision to drive. It takes a significant jump in the price-per-gallon of gasoline to dissuade most people from driving.
Meanwhile, goods or services that could be considered extravagant or indulgent are often the first items trimmed from a budget. Spa treatments, for example, would be among the first expenses most people would trim if they had to scale back their spending.
These are extreme examples of price sensitivity, and most goods or services will fall firmly in between these two examples. Analyzing customer spending data can help a small business determine exactly how to price a given good or service, as well as when to increase advertising or drop the purchase price.
Once a company understands how sensitive their goods or services are to fluctuations in price, the company can then tailor their marketing strategies accordingly.
As one example, many companies tend to lock their prices during the holidays, when emotional spending is at a peak and customers show less discrimination in purchasing. Other companies go the opposite direction, slashing prices and increasing advertising to move additional volume.
In either case, analyzing and interpreting big data can help businesses of any size identify the spending trends of their customers. This can help any business leverage the market from both an advertising and production perspective.
4. Gain a Complete View of the Customer
Big data doesn’t only showcase trends in spending – it can also provide insights such as why a customer might switch brands or services, or what a customer’s preferred shopping experience might look like. Both insights can help a small business better service their overall customer base.
Once a business has a full view of the customer, a business can then tweak its products, services, and marketing schemes to better satisfy the customer. Customer feedback data can be used even more effectively in this regard, and small businesses can give their customers exactly what they want.
Better satisfaction leads to increased retention and sales, both of which contribute to immediate and sustained growth. The use of data to fully understand the average customer is a great way for a small business to leverage the market through data analysis.
Moreover, small businesses can leverage big data to deliver the appropriate marketing campaign at the right time via the proper channel. A paper-heavy promotional campaign might fall flat if the average customer is a tech-savvy 20-something.
More-complete customer understanding can skirt this issue, leading to more effective uses of time and marketing dollars.
5. Targeted Mailing Lists
Businesses that continue to use paper marketing and promotional materials incur the cost of producing these materials. Smaller businesses on stricter budgets will need to be especially aware of these expenses.
Careful data analysis can help businesses determine which customers are actually buying and utilizing their products or services, and small businesses can create targeted mailing lists as a means of driving sales.
It makes little sense to send promotional flyers to people who have no intention of using a given product or service. Analyzing big data and distributing marketing materials accordingly are not only more effective, but also much less-costly, than the shotgun approach.
Grow a Small Business with Big Data Analysis
For a litany of reasons, it’s in the interest of small business owners to think before they act. This idea is no more apparent than in the analysis of big data.
While data analysis can cost a business owner a bit, these costs are often fractional compared to the costs of an ill-informed market campaign.
Moreover, big data analysis can teach a business owner more about her or his customers, leading to improved product development and ultimately increased growth.