How Big Data Can Help Small Business
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How Big Data Can Help Small Business

Big data is having quite an impact on the marketing world.  How should your small business use big data to improve your marketing efforts?

First off, it’s important to realize that all businesses, both big and small, can benefit from analyzing data about their customers and the way they react to products, services, and marketing efforts.  Data allows companies to market in a way that is more personal and interactive, going beyond traditional print to social media interaction and email outreach. Although you may assume that big data is better suited to large companies, small businesses are especially likely to benefit from insights gleaned from big data because their data sets are smaller, making it potentially easier to sort through and organize.

Here, without further ado, are a few potential benefits of analyzing all kinds of data related to your own small business (backed up by images from University of Alabama at Birmingham)

1. Boost Your Efficiency


Have you ever taken the time to really understand what it is that each person in your organization does, and subsequently tried to make those individual or department-wide tasks more streamlined and easy to accomplish?  There may be more efficient ways to conduct research or produce your products or services.  For example, many companies who do roofing work utilize Google Earth, now, to help them make estimates without necessitating an in-person consultation.  This saves the company a great deal of time and energy that, as a result, can be spent elsewhere.

Likewise, for more office-bound work, there are probably tasks that could be automated or accomplished using an alternate, more efficient method that you may not realize until you do a careful, detailed analysis of all the components that go into everyone’s day-to-day schedules.  You might try seeing how long each weekly tasks tends to take, then having teams conduct periodic research into different ways of accomplishing the same task.  For example, with email marketing, a well-executed A/B trial and error with different email templates and subject lines can go a long way toward the difference between 25 and 50 percent conversion rate.

Related: Big Data’s Most Influential Rock Stars: 10 Must-Follow Leaders

2. Cut Your Costs


Continuing with the theme of skipping unnecessary steps, another potential source of savings may be found in comparing contractors’ maintenance charges against the average of other vendors who perform the same service.  This kind of price checking saved Twiddy & Company Realtors $50,000 over two years, which equated to a 15% savings in their overall expenses—not a small percentage, by any means!  Similarly, it would be relatively painless to go through and see if there are any services performed by contractors that might be taken care of in-house, at no additional charge, or become automated—hence saving time and money.

Another way to cut costs is to do some analysis of which products and services are most popular with your customer base, and to eliminate unnecessary features or tasks in order to save on the expense of those particular expenditures.  Another example is posting customer surveys on Facebook and Twitter about various products and services, and seeing which are the most and least popular, then eliminating the most unfavorable features from production.  In doing this, you will eliminate unnecessary time and expenses from your budget.

3. Improve Your Pricing

Start by looking at sales performance: the more sales a product achieves, the higher the price point can potentially be.  For example, Uber has actually developed their own data-informed system of pricing, which it calls “surge pricing.”  The way this works is basically based on supply and demand: the more demand for a particular night or time of day, the higher the price range—and vice versa.

Hotels have also adopted data analytics in offering differentiated pricing; however, with them, the differences in pricing can be incredibly personalized and specific, depending upon prior purchasing patterns.  Data Science Central gives the example of a hypothetical customer, Jeff, booking a room for a personal trip to Hong Kong.  There is a surprising amount of data available on Jeff via third parties and his “StayScore,” a hotel industry-specific guest rating metric for how important a particular guest is to a particular region.  Based on all the above information, he is offered a selection of rooms in his price range.

4. Ensure You Hire the Right Candidates

Apparently data is now being used to help evaluate job candidates before they even step foot into your HR office!  Recruiters are evaluating certain pieces of information about applicants in order to help determine their potential longevity, for example, or who has the most creativity or skill.  There are sometimes surprising connections made between seemingly irrelevant details, such as the type of browser a candidate uses to fill out an application being connected to their job performance or tendency to job-hop.

Data analysis can also help evaluate applicants’ qualifications and skills through scanning resumes for concepts and phrases—as opposed to merely skills or buzzwords.  There are also structured assessments that may help evaluate desired personality traits or potential job performance.  One advantage of data is that it is objective and fact-based, rather than subjective and open to potential misjudgments and personal biases.


5. Help You Compete with Big Businesses

At times, small businesses may feel dwarfed by big box stores and imposing competitors with more online presence and brand name recognition.  It’s not necessary to feel left out, however; you might consider mimicking the big business strategy of utilizing predictive analytics in order to “better understand their customers, predict trends, inform strategic decision-making, and improve overall business performance, according to research firm TDWI Research.”

One impressive and also slightly disturbing example of predictive analysis can be found in Target’s recent tracking of data in order to determine that customers may be pregnant.  In one case, Target managed to guess that a young girl in high school was expecting before her father caught on to the situation!  They did this by comparing customers’ purchases with a list of 25 products frequently associated with new and expectant mothers, such as calcium & magnesium supplements and fragrance-free cleansers or lotions.

Get your data!

With a little planning and foresight, you can put big data to work for you.  There are a variety of cloud-based options that can eliminate the need for data storage capacity, and small businesses usually have less data to work with, so the possibilities for different platforms and options for data analysis are plentiful and varied.

Get researching, and post your own small business data findings in the comments below! We’d love to hear how you make use of data.

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