In a world run by large corporations and monopolies dominating nearly every target market, small businesses are forever struggling to carve a place out for themselves.
The only way to cut through the noise and grab the attention of your target audience is to optimize your customer experience every step of the way and make the most out of every marketing campaign.
But how can small businesses do this without expensive and time-consuming trial and error?
The answer: Data
When small businesses fully embrace data by learning how to collect it, transform it, and analyze it to predict future trends, they can stay ahead of the curve and avoid making expensive or survival-threatening mistakes. The power of foresight should never be underestimated.
In light of that, let’s find out how small and medium businesses (SMBs) can leverage predictive analytics.
What is Predictive Analytics?
As its name suggests, predictive analytics refers to predicting future outcomes based on historical data. In other words, it’s the method of analyzing past trends to predict where they’re going. This can be achieved using data, statistical algorithms, AI, modeling, and machine learning techniques.
Predictive analytics uses both structured and unstructured data based on a variety of metrics to generate insights. Structured data includes figures readily available for analysis, like age, gender, marital status, income, and customer sales. On the other hand, unstructured data is textual data that isn’t immediately quantifiable, like social media content, call center notes, or different types of open text.
Both data types are used in the predictive model to empower businesses to gauge where trends are going.
Predictive Analytics works in five simple stages:
- Data is collected.
- The information is formulated into reports and analyzed.
- Data is monitored as it transforms over time.
- Predictive algorithms are used to make educated guesses about future events.
- The business takes action based on these predictions.
This last point is what we’re discussing in detail in this article. More specifically: what actions can small businesses take based on predictive analytics, and how can they benefit from this process?
Let’s find out…
1. Identify New Trends and Opportunities
Developing product ideas with high demand and low competition is crucial to any thriving business.
This is where data is worth its weight in gold. With the proper market research, you’ll soon get an accurate feel for how much interest there is in your product idea. Today marketing is driven by tools in your martech stack, which are in turn driven by AI. Predictive analytics uses hundreds of data points hitherto not available to SMBs to create an accurate model of the customer journey.
Predictive analytics can pinpoint the types of products and services that are likely to be accepted and demanded by customers, based on emerging trends and buying habits. This, in turn, allows you to tailor your messaging at each stage of the buyer funnel for maximum engagement.
Traditionally, it was difficult for SMBs to beat big brands with deep pockets who not only rode the trends but also defined them. But now, a small business can give the behemoths a run for their money, at least in sectors like retail and ecommerce. Predictive analytics lets you target the most profitable customer segments and provide additional information or deals at the right times to increase the likelihood of purchase and brand loyalty.
2. Generate Accurate Sales Forecasts
Accurate sales forecasts are handy for any small business. For one, they’re crucial for calculating your overheads and budgeting. When you know how many sales you’ll likely bring in, you’ll have a clearer understanding of
- how many customer support agents you’ll need
- whether you have enough inventory for seasonal events
- how to plan for sustainable growth
These are just a few examples, but you get the idea. Predictive analytics-based forecasting makes these kinds of reports possible for businesses of all sizes across industries. The models automatically adjust for new variables and change their forecasts whenever new information becomes available, drawing on historical and current sales data. That way, you and your team can be confident that you’re taking into account all the latest factors while making decisions and planning for demand.
3. Reduce or Optimize Costs
Predictive analytics is critical for reducing business costs. For instance, we’ve already touched on how they help predict how much inventory you’ll require and how many staff you’ll need. Knowing this ahead of time enables you to order the right amount of stock so that it doesn’t sit on the shelves and cost you. You can also make sure you aren’t hiring permanent staff for a temporary job, who might end up warming the benches in your organization once the project is complete.
The same principle applies to resources that you use. Reports from Flexera, IDG, and Nutanix indicate that over 90% of companies today use some form of public or private cloud systems for their IT departments. It is very difficult to estimate the exact compute, storage and networking resources you’ll need over your subscription period, and you might end up overpaying for it or purchase more hardware or software than necessary.
This is where predictive analytics can help optimize costs in IT. Here you can see which tech actually maximizes ROI so that you can prioritize your budget according to your preference for upfront capital expenditure (CAPEX) or ongoing operational expenditure (OPEX). Additionally, with data about resource efficiency at your disposal, you’ll also be able to identify where your IT processes need improvement and make the necessary improvements.
Data-driven enterprises frequently report better cost-efficiency as a major benefit. Improving the quality of data that your business uses could save up to 25% of your revenue, as per a report in the MIT Sloan Management Review.
4. Deliver Better Customer Service
It’s no secret that often, customer service is where small businesses have the edge over larger organizations. Again, predictive analytics gives a great business advantage. For example, it can identify peak and slack times for customer support requests and businesses pressed for staff can simply ensure more or less agents are available at these times.
With more businesses moving online every day, a significant number of companies interact with their customers mostly via digital channels – who calls a customer service number these days when we have Twitter and Facebook? Predictive analytics helps make the digital customer experience smoother by measuring and tracking the service quality on three fronts: availability, functionality, and speed.
Predictive analytics can also identify more complex patterns, like events or times when product failures are more likely to happen. With this information, your business can schedule maintenance sessions with customers before issues occur.
Another use of predictive analytics is to create a model to predict customer churn. Some customers present a high “churn risk”; predictive analytics can identify these customers based on event triggers and passage of time. This would guide you on the best possible times and incentives with which to re-engage these customers before they lose interest.
Looking to the Future
Putting in place processes, models and tools that use predictive analytics is vital for small businesses. From ensuring budgets are used wisely to supporting IT teams, predictive analytics helps prevent mistakes, find new opportunities, convert more leads, and increase brand loyalty.
Is your startup or small business finding innovative applications for predictive analytics? If not, you now have a few ideas on where to start. Good luck!