Big data has quickly become a game changer for small to mid-sized businesses (SMB).
Chances are, you’re already analyzing data to gauge where your company stands against the competition. That means you might already be using some big data tools to make insights and discover trends.
As a matter of fact, Nielsen surveyed 2,000 U.S. small businesses and found that 60% of them use big data to identify opportunities to update product and service offerings.
But what if you could start predicting customer behavior and market trends rather than just reacting to them? That’s where predictive analytics comes in.
Large Corporations vs. SMBs
Predictive analytics sounds like something for giant corporations and enterprises. But it’s actually a branch off of big data, which is more about relating disparate data than the volume of it.
The simple truth is every business, big and small, can leverage predictive analytics.
But that’s not to say that there’s no difference at all. SalesClic’s CEO of sales visualization and analytics, Thomas Oriol, told DestinationCRM.com that the biggest difference between large and small business predictive analytics is the ability to have internal data scientists and analysts to calculate the numbers and analyze the data. Since small businesses don’t have this luxury, “you have to incorporate interpretation into the product itself,” he said.
Many big data vendors have caught on to this and have created tools that cater to the needs of small business. Hyperlocan media, events and research company, Street Fight has listed five notable ones:
- Canopy Labs
- Stitch Labs
- Watson Analytics
Benefits for Small Business
There are many benefits of predictive analytics for a growing company. The top two are customer retention and demand forecasting.
It’s cheaper to keep your loyal customers than to get new ones hooked.
With predictive analytics, you can track and analyze customer behavior to predict what and when a customer may buy, and recognize the customers at risk for leaving.
Small business predictive consultants SimaFore also note that an important benefit for new businesses is to “identify which prospect groups are most likely to adopt their products and services.” This allows companies to recognize opportunities for expansion, as well as effectively use their marketing budget on promising targets.
Success with Windsor Circle
Windsor Circle, a leader in customer retention and predictive marketing for online retailers, helped the largest coffee provider for Philadelphia’s Coffeeforless.com and Australia’s top surf and apparel retailer SurfStitch keep their customers coming back.
Originally founded as a family business, Coffeeforless.com has used Windsor Circle’s predictive data to send emails to loyal customers.
Once a customer has purchased from the online coffee retailer three times, Windsor Circle automatically cues up a predicted order date and triggers a “replenishment email” with products based on the customer’s purchasing behavior, as well as similar products the customer may want to try.
Starting out as a backyard garage start-up, SurfStitch uses Windsor Circle’s predicted order date feature to identify customers at risk for leaving.
Instead of using static dates to launch a win-back email campaign, SurfStitch sends the email on the predicted order dates with a message based on the individual’s buying habits.
As a SMB, you usually know what your regulars want before they say it. With predictive analytics, you can make every customer feel just like a regular.
Although predictive analytics can help SMBs take their personal touch to the next level, it also allows large corporations to offer personalized customer service as well.
For small businesses, growing the top line has always been a priority, but now that their customer service is being matched or surpassed by larger businesses, it has become necessary to survive.
Inventory tracking and effectively forecast which products or services are most in demand at a certain time of the week, month, or even year can improve the top line of a business significantly.
How Stitch Labs Helped
Passionate about providing intuitive inventory solutions for online retailers, Stitch Labs has given small businesses the ability to effectively forecast their inventory needs.
Fair-trade handbag boutique Purse & Clutch uses the online inventory solution to keep track of which items are sold and which handbags have become bestsellers. Finding patterns in customer behavior based on past and current sale data, the shop can prevent selling out of any certain item by predicting what inventory it needs to purchase.
How to Get Started
When it comes to big data and predictive analytics, cost isn’t as much of a problem now that there are more low-budget and open-source solutions to choose from.
The biggest problem lies with companies not knowing how to get actionable insights from the data they extract. In fact, in the Nielsen study mentioned above, less than 15% of the small businesses surveyed knew how to do this well.
How can a small business make sure an initiative will yield actionable insights? Start with a specific goal in mind or a problem that needs fixing.
Beginning with a specific objective, such as wanting to sell more of a certain product or service, will start you off with a smaller data range and scope rather than staring at thousands of data points and hoping something will jump out.
After creating a well-defined objective and finding the most useful data, you can then identify how to measure the key performance indicators, and begin using a tool that suits your company’s needs.
Amulet Analytics’ senior data scientist Daniel Gutierrez came up with four key points for how to take full advantage of a predictive analytics initiative:
- Have a clear strategy for how to use data and analytics.
- Have the ability to identify, manage and combine different data sources.
- Be able to build machine learning models for predicting outcomes.
- Have management transform the organization from process-based to data-based decision making to have better results.
One last thing to keep in mind is that even though all businesses can leverage the power of predictive analytics, it doesn’t mean that it’s the correct solution for every company. Make sure to find proof your company needs predictive capabilities before jumping in head first.