Small-to-midsize businesses can now take advantage of some of the predictive analysis tools previously reserved for big brands.
Big Data and predictive analytics is an example of this dynamic at work. Both are a perfect fit for smaller companies, particularly since cost is no longer a barrier to entry. Today, we’ll explore predictive analysis tools specifically geared for SMBs, and also how this technology applies to VoIP call centers.
Applied to SMBs
Predictive analytics is used to make predictions about unknown future events. As such, it uses data mining, statistics, modeling, machine learning and artificial intelligence to analyze current data to surface targeted outcomes and trends. For SMBs, these types of predictions can generate custom offers based on customer preferences and purchasing histories.
Predictive analysis does not tell a small business owner what willmight happen in the future. It forecasts what happen in the future with an acceptable level of reliability, coupled with what-if scenarios and risk assessments. For future probabilities, predictive models combines current data with historical facts to assess a better understanding of SMB customers, products and third party partners.
Machine-Learning for Smaller Businesses
Created for SMBs that can’t afford traditional big data technology, the software ‘BigML’ zeroes in on data that companies already have collected.
Their hosted machine-learning platform finds relationships and patterns with pre-existing data sets to predict customer churn. BigML’s tools can also be used to create those data sets. The ’confidence values’, which surfaces as a result, will assure the company the certainty of all of the predictions that BigML surfaces.
Their service focuses on taking the complexities out of creating a high-availability, low-latency machine-learning system, personalized for an SMB’s specific needs.
Priced economically for the smaller firm, projects tasks that come in under 16MB are free, and for premium services, monthly subscriptions range from $30 to $300 per month.
Better Inventory Purchasing Decisions
Early in 2016, Stitch Labs launched a sales forecasting tool for small local merchants. On their website’s ‘operations command center,’ Stich provides businesses with a holistic overview of one’s business where they can cost-effectively increase efficiencies and scale one’s operations more intelligently.
Using a combination of predictive technology and customer order histories, Stitch Labs assists small businesses in the retail field to make better purchasing decisions, and allows them to accurately forecast future sales.
Retailers using this software can project sales in four or 12-week periods, and Stitch Labs differentiates itself from competing hyperlocal solutions by using “an internal data cluster,” rather than third-party plug-ins. Starter plans start at $29 per month.
VoIP Call Center Analytics
There’s a world of difference between traditional call centers of yesteryear and those, which use the technological advancement of VoIP in the digital age.
The US Contact Center Decision-Makers’ Guide is the culmination of survey predictive analyses from 210 call centers around the United States in a variety of industries. The study examines issues, concerns, and data relating to call center management and evolution, including trends and forecasts, for all major areas of focus, such as performance, investment, technology, human resources and strategy.
High on the list are advances in speech analytics, which can help improve call center CRM (customer relationship marketing) by addressing telltale vocal features (such as inflection, intensity, or tone) long ignored by call recordings and transcripts. Talk-over analysis can also determine trouble spots and alert supervisors of potential issues immediately. Where simultaneous crosstalk can indicate or create frustration, talk-over analysis can also analyze CRM agent silences that can pinpoint knowledge gaps and opportunities for additional training.
Still In Early Stages
The usage of predictive analytics for small business is still in its infancy stage. But the market is growing as small business owners become more comfortable integrating these technologies into their business practices.
According to a 2014 report by TWDI Research, 58% of businesses that use predictive analytics today use it for direct marketing, and 55% use it for cross-selling or upselling purpose.
In future posts, I will be highlighting additional predictive analysis tools for SMBs, as they hit the market.