In the coming years and beyond, real-time business intelligence and analytics will continue to drive new business models, increase insights into customer behavior and be one of the primary catalysts driving a revolution in selling, manufacturing and service. From the algorithms they use to the applications they power, companies of all sizes will have a chance to capitalize on real-time intelligence by leveraging business analytics tools. We’re going to show you 10 ways in which real-time analytics is driving these trends.
- Forrester forecasts a 15% compound annual growth rate for the predictive analytics and machine learning market through 2021, according to their recent study.
- Between 2017 and 2019, spending on real-time analytics will grow three times faster than any other type of analytics and will be worth $22.8 billion by 2020, according to a recent Gartner study.
- Real-time business intelligence analytics that enables cross-functional collaboration across departments, divisions and teams is the most valuable feature in the leading companies, according to Gartner.
1. Maintaining more responsive, transparent relationships with customers across all channels will increase retention rates and drives up revenue.
There are many academic and industry studies that show both B2B and B2C customers now expect real-time responses to their requests and transactions. Amazon, Facebook, Twitter and many other social media and high-performance eCommerce sites are fueling these expectations. For any company to compete, real-time analytics is a must, as it drives revenue.
A study recently cited by MarketingProfs found that just 1% of shoppers who return for a subsequent visit to a site increases overall revenue by approximately 10%. The study projects that if online retailers retained 10% more of their existing customers, they would double their revenue. The post concludes by saying that reducing customer defection rate by just 5% can increase profitability 25 to 125%.
2. Real-time data is driving greater revenue opportunities with machine learning.
Real-time business intelligence is enabling more rapid improvements in the automotive, consumer, energy, and transportation and logistics industries. McKinsey analyzed the data richness associated with each of the 300 machine learning use cases, defining this attribute as a combination of data volume and variety. The heat map shown below is a part of their final report. McKinsey Global Institute’s study, The Age of Analytics: Competing In a Data-Driven World, provides valuable insights into where real-time business analytics is making the most impact.
3. By 2021, at least 75% of retailers anticipate investing in predictive analytics for loss prevention and price optimization.
Retail is one of the most brutally competitive industries there are today. Real-time business intelligence gained from the internet of things are predicted to have a transformational effect on the industry as a whole. According to the Forbes, real-time business intelligence obtained from IoT-based strategies will drive greater accuracy in key retailing areas, including market-basket analysis, customer segmentation, and centralized customer data and intelligence.
4. Analysis of complaints, customer suggestions and product line extensions is streamlining product roadmaps and reducing time to market.
It’s often a company’s greatest critics that deliver the best ideas for new products and ways to improve existing ones. The use of real-time analytics of returns material authorizations, warranty repairs and rejected products is an invaluable source of new ideas on how to improve. Using real-time analytics, critics can be the best collaborators when it comes to new product development and the successful launch of new revenue strategies.
5. By using real-time business intelligence and analytics to define the best possible product configurations, sales cycles are being accelerated while greater revenue is obtained.
Sales teams often stay with the most popular product configurations and options when creating quotes for new and existing customers alike. Actual-time business analytics is making it possible to provide sales teams with the guidance of just a small shift in product configurations, upsells and cross-sells, each of which has a major impact on revenue. Adding real-time analytics to guided selling applications drives immediate revenue while reducing order capture errors.
6. In using current analytics, companies are reducing contract, quote and order errors.
Configure-price quote adoption is accelerating due to the ability of real-time business analytics to guide sales teams at every stage of creating quotes, product configurations, contracts and pricing. Orchestrating pricing, contracts, payment, delivery and service schedules are all benefiting from real-time business intelligence. Based on the insights gained from real-time analytics, CPQ is scaling across a broader base of selling channels as well. The insights gained from customers from online channels are further revolutionizing how companies sell today.
7. Real-time business intelligence is changing the nature of pricing strategies, allowing for a more precise measure of price elasticity by persona, sales channel and timing of special discounts.
Real-time analytics is a catalyst that is changing how pricing is defined, implemented and measured across business units and sales channels. It’s making it possible to determine the best possible timing for pricing specials, knowing that customer behavior is different at the end of a quarter versus the beginning. Amazon uses data to portray themselves as the low-price leader even when they aren’t, as this Business Insider article points out.
8. Improving service call close rates while providing guidance on which products and services are best to upsell and cross-sell is becoming more attainable with real-time business intelligence.
Up-to-the-minute analytics combined with location intelligence is revolutionizing field service call management, leading to more closed service or trouble tickets on the first visit. For cable companies, this is a major accomplishment, as it often can take at least three visits to close out an enterprise business’s many telecom requirements and needs. Salesforce is a leader in cloud-based service call management, with many software vendors providing solutions on their AppExchange. The Salesforce cloud architecture now supports real-time analytics integration, making it possible to create dashboards and scorecards showing activity as it happens, predicting the best possible outcomes.
9. Improving perfect order performance by using real-time business analytics to forecast demand.
One of the most valuable insights business analytics can provide for manufacturing companies is improved forecasting accuracy and corresponding delivery dates. When manufacturing intelligence systems are designed to deliver real-time analytics for each step in order and product fulfillment, perfect order performance improves, revenues go up and costs decline. Real-time business analytics integrated into manufacturing intelligence systems are revolutionizing production centers from the shop floor to the top floor.
10. Business analytics is predicting which fulfillment, service and support strategies will deliver the greatest contribution to net promoter score improvement.
Despite the debates that seem to continually swirl around net promoter scores, it is a metric based on a customer-centric methodology. Using real-time analytics to understand which strategies to emphasize and when to emphasize them can have a significant impact on turning detractors into promoters over the long-term. Measuring customer satisfaction will continue to improve as real-time business intelligence gains greater adoption and becomes more robust in its analytical scale and scope.
Final Words on Real-time Business Intelligence Trends
Real-time business intelligence has already had a massive impact on global revenue. They’ve transformed nearly every aspect of what it is to be a modern enterprise. With access to things like KPIs, heatmaps and sophisticated analytics models, decision makers are able to not only get a clear picture of their business, but are also able to diagnose (and in many cases cure) their specific professional woes — all to the benefit of their bottom line.
As real-time analytics becomes more robust, we can only expect global revenue to skyrocket simply due to what real-time analytics can do for a business. If your company hasn’t already made the investment in business analytics software, SelectHub can help you pick from hundreds of vendors to find the right system for you.
Did we miss anything? How else are real-time business intelligence and analytics driving revenue for your business? Let us know in the comments below!