In 2018, real-time 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 to the applications they power and the systems they enable, companies of all sizes will have a chance to capitalize on real-time analytics.
Business Analytics Trends
- Forrester forecasts a 15% compound annual growth rate (CAGR) for the Predictive Analytics and Machine Learning market through 2021, according to their study The Forrester Wave™: Predictive Analytics And Machine Learning Solutions.
- Between 2017 and 2019, spending on real-time analytics will grow three times faster than any other type of analytics, according to a recent Gartner study.
- Real-time business analytics that enables cross-functional collaboration across departments, divisions and teams is the most valuable feature in the leading companies listed in Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms.
Real-Time Business Analytics Scale, Speed & Usability Are Key Success Factors
When evaluating real-time analytics applications that have the potential to drive revenue, consider how well they can scale across cross-functional teams and departments first. Enabling greater collaboration and knowledge sharing is essential for making product introductions successful, as it’s one of the most important revenue strategies any company undertakes. Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms accentuates how important scalability is. Scale is a key success factor for any real-time business analytics app to deliver value, as it enables cross-departmental and cross-divisional collaboration and knowledge sharing.
Research into just how “real time” the application is and if its underlying technology stack is built for integration and speed is another important consideration. It’s a bonus if the applications you’re looking at are created using Angular JS, which is the language Google uses to develop its applications.
In the highly competitive real-time business analytics market, usability is also one of the most differentiating and valued features across the many companies competing today. Ironically, real-time analytics delivers the greatest value in an enterprise’s most complex applications, yet is the least represented within them.
Supply Chain Management (SCM) applications and the strategies they support trail other enterprise application categories. The situation in SCM is so urgent, Gartner published a research study, titled What’s Wrong With Your Supply Chain Planning Technology? Focus on Its Usability, just on this topic.
The following are the ten ways real-time business analytics are driving revenue today, and will accelerate in 2018:
1. Creating and continually improving more responsive, transparent relationships with customers in real time across all channels increases 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 are a must, as they drive 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, according to a recent McKinsey & Company study. Real-time business analytics are enabling more rapid improvements in the automotive, consumer, energy and transportation & 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 provided 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. The following heat map illustrates where real-time business analytics and optimization are making the greatest contributions:
3. By 2021, at least 75% of retailers anticipate investing in real-time predictive business analytics for loss prevention and price optimization, in order to improve the overall customer experience. Retailing is one of the most brutally competitive industries there are today. Real-time business analytics gained from the Internet of Things (IoT) are predicted to have a transformational effect on the industry as a whole. According to the Forbes, real-time business analytics 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. Using real-time business analytics of complaints, customer suggestions for new features 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. Using real-time analytics of Returns Material Authorizations (RMA), 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 of all in new product development and the successful launch of new revenue strategies.
5. By using real-time business analytics to define the best possible product configurations and options to sell a customer, 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. Real-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 have a major impact on revenue. Adding real-time analytics to guided selling applications drives immediate revenue while reducing order capture errors.
6. Reducing contract, quote and order errors by becoming the foundation of Configure-Price-Quote (CPQ) and Quote-To-Cash (QTC) platforms and the selling strategies they support. CPQ 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 analytics. 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 analytics are changing the nature of pricing strategies today by having 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 define the best possible timing for pricing specials, knowing that customers’ behavior is different at the end of a quarter versus the beginning. Amazon uses real-time analytics 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 analytics. Real-time 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 and on time delivery accuracy. One of the most valuable insights real-time 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. Predicting which fulfillment, service and support strategies will deliver the greatest contribution to Net Promoter Score (NPS) improvement using real-time business analytics drives long-term loyalty and customer value. Despite the debates that seem to continually swirl around NPS, 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 analytics gains greater adoption and becomes more robust in its analytical scale and scope.