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Even Small Businesses Can Boost Their Bottom Line Using Big Data

Big data has been that ‘thing’ sitting in the corner of the room for years, ignored and -as some business professionals might admit- hoped it would finally leave on its own. It can be overwhelming trying to make sense of a mountain of information, numbers and stats, dates and figures that, at the end of the day, don’t amount to anything of real value to begin with.

Data is Power

Businesses have long held onto a massive amount of information -or data- and did nothing with it. Much of that information involved sales data, what their customers purchased, how often they visited their store, what times were best, and so on. Unfortunately, for many of those older companies, this information was often stored on paper and it usually found the bottom of a box or file cabinet that was eventually tucked into a basement storage facility for ‘safe keeping.’

The Potential is Endless

However, thanks to technology, we no longer have that dilemma. Of course, we are inundated with more information than ever, and sadly too many businesses still feel as though it’s all just a monster lurking in the office, waiting to pounce.

Big data can certainly overwhelm, but it has incredible potential … if it’s organized and utilized properly.

The key crux of the problem -how to utilize it properly.

Some small businesses have discovered through trial and error (and not to mention a fair amount of sheer will) that the big data they collect could help them market better, target their audience more effectively, and determine what methods just weren’t having the effect they initially hoped it would.

Case Study #1: Vacation Rentals – Twiddy.com (Duck, NC)

In a sleepy seaside community, popular anytime between May and September, Twiddy, one small rental agency that was responsible for booking many of the units on the island continued to struggle to make sense of various lulls … right smack dab in the middle of summer.

By seeing the seasonal trends and recognizing when vacationers were less likely to look at renting on certain weeks, the company was able to recommend to their clients reducing the prices, which eventually led to an increase in bookings.

Twiddy’s owner admitted that they had this data already in their midst for years, but because they never bothered to look at it, they didn’t recognize those patterns or trends. It was assumed that weather or when certain holidays feel (ie. on weekends, mid-week, etc.) were causing these patterns of rental behaviors to change and, with those assumptions, it felt as though it was just a matter of chance -or bad luck- that some weeks didn’t ‘book’ as well.

Taking advantage of the data it had on hand, the company managed to increase bookings by encouraging its clients to adjust rental prices based on the fluctuations that happened every single year.

Case Study #2: Car Sales – Carvana (Phoenix, AZ)

It’s no surprise that car sales online is a major market, though consumers are still wary about purchasing a vehicle sight-unseen. No one wants to simply take the recommendations of a used car dealer without getting some specifics and even test-driving it.

Yet, more and more people are turning to online car sales outlets to shop for better deals. One company, Carvana, decided to put Big Data to work for it, recognizing the value in not only finding the best deals at auction, but also helping to weed out suspect buyers.

Using the services of some highly trained and experienced analysts, this company managed to reduce the risk of buying ‘lemons’ at auction, but also found a way to get better quality, more reliable vehicles for less than what similar cars were selling for at other auctions.

This small business also focused on a broader metric when it came to financing for their customers. Instead of simply looking at the credit score, they analyzed a number of other outlets to determine which potential customers would be considered ‘high risk’ for default or fraud and thus avoiding doing business with such individuals.

By focusing on more reliable cars and fewer defaults on loans, Carvana not only saved money year after year, it also began earning a reputation of being a quality used car dealer online. Big Data helped this company rise above its competition -for both online and in-person used car dealerships.

Case Study #3: Accounting and Bookkeeping – Xero.com

If a company processed over $1 trillion in transactions for clients around the world, it’s a pretty safe bet they have a lot of data. But Xero, a global accounting and bookkeeping firm that’s been helping businesses large and small manage and grow their operations understands the impact big data can have.

As Xero Australia’s Managing Director Trent Innes explained during a seminar the company hosted, “The opportunity to access a more complex customer picture may sound like a run-of-the-mill development, but its impact is very real and far-reaching. Broader range insights are rewriting key business touchpoints -improving customer experiences, business efficiencies, and the hard-earned competitive edge.”

The key, according to the company, is in having the right tools and utilizing them effectively. There are numerous tools readily available, but sometimes it can feel overwhelming figuring out how and where to start.

Xero has managed to put big data to work for its operations, understand demographics and even government policy, and how to best make it work for its operations.

But What About the Cost?

The cost of organizing big data is one of the key reasons many small businesses balk at taking action. Instead of focusing almost exclusively on the cost, though, it’s important to understand the return on the investment.

In the examples above, each of these businesses had to invest in Big Data, to get it organized and understand what it offers. When they did, all of them enjoyed financial reward. For the vacation rentals, an investment of $40,000 returned $60,000 in savings and increased rentals in less than a year (it had hoped to recoup the cost within three years). For the online car sales, they wouldn’t release their numbers because of competition, but the initial investment paid for itself in a matter of months.

It’s something each business must confront for themselves, but ignoring big data can lead to incredible missed opportunities.

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