CPQ strategies continue to bring greater accuracy and speed to every aspect of sales cycles, from pricing to product configurations. Considered to be one of the hottest areas of Customer Relationship Management (CRM), CPQ strategies are unique in that they provide unequivocal evidence of their value across an enterprise. The more complex the sales cycles, product configurations and channel selling structures, the more CPQ selling strategies pay off. Gaining greater insights into customer requirements and being able to quickly anticipate and act on their needs is essential for winning additional deals. CPQ is the catalyst of sales growth many companies need to excel at, as every aspect of customer relationships is becoming more complex, faster and more context-driven than ever before.
Some quick facts:
- Gartner predicts the CPQ market will continue to grow at a compound annual growth rate (CAGR) of 20% through 2020 in the Market Guide for Configure, Price and Quote Application Suites.
- Cloud-based CPQ revenue is now approaching the majority of the market and will accelerate through 2020, redefining the landscape of this market according to Gartner’s Market Guide for Configure, Price and Quote Application Suites. As of 2015 the market was valued at $157B, projected to attain solid double-digit growth through 2020.
- 83% of sales professionals are using some form of Configure-Price-Quote (CPQ) systems today, according to Accenture Interactive’s recent study, Empowering Your Sales Force: It’s Not Just Automation, It’s Personal.
CPQ Is Redefining Sales Effectiveness
Progressing beyond product configuration and making sure the orders sold by sales teams are reliably built, CPQ today is the foundation creating an entirely new era of sales effectiveness possible. Every aspect of the sales cycle is being improved by CPQ today. Of these areas, the two with the greatest potential are pricing and managing products throughout their lifecycles. Despite the hype surrounding analytics, Big Data, and machine learning, there’s ample evidence these technologies are delivering insights that drive more profitable selling strategies. The decision-making process for prospects changes over a given quarter or year. The more urgent the need is to solve a problem with pricing and profit implications, the faster the sales cycles move. CPQ is proving to be a very effective cloud application that takes on these challenges and turns them into opportunities.
Sales effectiveness is also being revolutionized by the rapid advances in user interface design, intuitive workflows that can quickly be modified to match how companies work, and mobile-first application design. The mobile-first mantra that so many CRM companies, including Salesforce platform-based companies specifically, are adopting are paying dividends regarding faster, more contextually-aware applications. The three factors of user interface design, intuitive workflows, and mobile-first application design are also driving the highest levels of sales team adoption for the latest generation of CPQ applications. The evolution of the user experience is one of the most-needed innovations in the CPQ market as adoption has often been a challenge due to the inherently complex nature of product configurators and their related apps.
Accenture’s study, Empowering Your Sales Force: It’s Not Just Automation, It’s Personal provides a glimpse into how pervasive technologies are being used to streamline the selling process. It’s accurate from the standpoint of how sales professionals tend to be overwhelmed with the technology that’s supposed to help them gain closer contact with customers. Ironically, the study finds that sales professionals spend more time attempting to make technologies align with customer-driven initiatives than spending time with customers. This finding shows one of the most powerful trends happening in the CPQ market today, which is the consolidation and simplification of CPQ applications across entire platforms. This development is most evident in how the many CPQ vendors who have built on the Salesforce platform are attempting to broaden their scale quickly.
83% of sales representatives interviewed as part of the Accenture study are currently using CPQ applications today, and 81% are using technology-based tools to identify and take action on sales leads. 80% are using automated CPQ tools to provide prospects with quotes that include their product and service configurations. The following graphic compares the key findings from Accenture’s survey on sales effectiveness.
CPQ Is Streamlining OmniChannel Selling
It’s a daunting challenge for any company to provide a consistently excellent experience across every selling and service channel at all times. Given the services, product and support breadth that companies have, excelling at OmniChannel is especially difficult. Cloud-based CPQ applications have global scalability developed at the platform level, enabling them to flex in response to unique pre-sales, selling and service strategies. Below are a few examples of how CPQ is streamlining OmniChannel selling:
- Real-time pricing that is immediately accessible across all channels, all devices and sales teams globally. One of the most challenging aspects of OmniChannel selling is having all pricing databases current across all laptops, smartphones, and tablets. Cloud-based CPQ applications and the platforms they are based on are alleviating this problem by having pricing included at the system of record level. Cloud platforms are integrated with pricing databases for every pricing quote or request that arrives in the app, providing greater accuracy and consistency than could ever be achieved with a distributed pricing strategy. CPQ vendors continue to add in localized pricing options and support for the most popular currencies their customers are requesting, further transforming pricing into a strength of CPQ selling.
- A company’s selling catalog can be kept up to date on all product and service changes with just a single edit that is published simultaneously across all channels. As with pricing, sales teams often have multiple catalogs they are using at any given point in time. By having a cloud-based CPQ app orchestrate every aspect of product and service catalogs, just a single edit is needed to any entry. In real time, the changed content is reflected in every catalog, in every channel, immediately. Having product and service catalogs be the single source of truth across all channels drastically reduces quoting errors, accelerates deal cycle times, and ensures any order taken can be shipped.
- Cloud-based CPQ systems enable role-based data access controls to the partner and role level with greater accuracy than legacy channel selling systems. As any selling organization evolves from multichannel to omnichannel-based strategies and programs, the need for enabling greater role-based data access controls to the partner and role level become a priority. Partner Relationship Management (PRM) systems are capable of only providing limited channel partner controls. CPQ applications today are designed to enable channel-specific pricing, rebate management, deal management, team selling and revenue-sharing programs. By globally deploying a CPQ system capable of scaling to support the entire selling cycle, each role in the selling strategy can be made more effective while securing the most valuable data any company has to drive new revenue.
- Scaling promotions, pricing recommendations, deal scoring, upsell and dealer and selling incentives. When scaling to omnichannel selling strategies, the synchronization of incentives, pricing, deal scoring, upsell and cross-sell requires a single, unified system to manage across all channels. CPQ systems are scaling to support omnichannel incentives, promotions, special pricing, cross-sells and upsells more than ever before. Scaling omnichannel selling requires cloud-based CPQ systems that can react quickly to pricing, incentive, and product changes without slowing down any sales cycles. Analytics and insights derived from machine learning are also essential for making most profitable decisions at the best possible time in a sales cycle.
- Salesforce is taking the lead in applying Artificial Intelligence (AI) to improving customer relationships with Einstein. Expect to see CPQ vendors follow the lead. Salesforce Einstein is putting AI into the context of customer relationships at a fundamental level, making it possible for marketers and selling teams to understand contextual intelligence and gain needed insights. Apttus, Infor, Oracle, SAP and other vendors with CPQ applications are also pursuing AI. These are the forward-thinking CPQ vendors who see AI as a means to improve the customer experience and excel at each phase of their sales cycles. AI is the glue that enables the Intelligent Cloud Maturity Model shown later in this article to stay tightly integrated together.
CPQ Is The Rocket Fuel Driving The Era Of The Intelligent Cloud
Knowing when to offer specific price incentives, upsells or cross-sell promotions based on previous customer behavior patterns is becoming possible thanks to machine learning. By aggregating the massive amounts of data captured across transactions, marketing and selling teams are aggregating data sets together and using the combination of CPQ and machine learning to gain greater insights. These insights accelerate sales cycles, increase deal sizes and remove barriers to creating and closing more business. Taken together, they are the core components of the Intelligent Cloud, unified by the many approaches companies are taking to drive more sales using their CPQ strategies.
The following is just a few of the many data points that reflect how CPQ is revolutionizing selling, with the Intelligent Cloud being the platform of the shift in selling strategies:
- In just a year, the Cloud is predicted to be the most preferred mechanism for delivering analytics in the enterprise. (Source: IDC FutureScape: Worldwide Cloud 2016 Predictions — Mastering the Raw Material of Digital Transformation, Nov. 2015)
- 50% of B2B-based enterprises this year are planning to invest in predictive analytics solutions to improve prospect qualification, opportunity automation, forecasting automation or renewal management. (Source: Gartner, Evaluate Emerging Sales Performance Management Technologies to Improve Sales Execution, September 15, 2015)
- Analytics are essential or very important to enabling more effective business strategies and operational outcomes according to 9 out of 10 enterprise leaders globally. Also, 84% of high performers are projecting that the importance of analytics will increase either somewhat or substantially in the next two years. Source: Salesforce Research Defines The 2015 State Of Analytics. November 1, 2015
- 81% of enterprises are relying on analytics to improve their understanding of customers and their purchasing process. (Source: 81% of Enterprises Are Relying On Analytics To Gain Greater Customer Insights, Forbes, July 26, 2015)
Machine learning and predictive analytics combined with CPQ applications are accelerating a new era of intelligent selling, setting a strong foundation for the growth of the Intelligent Cloud, and delivering the following results:
- Faster, more accurate, profitable pricing that closes more deals faster. Machine learning provides the insights needed to define the optimal pricing strategy for each prospect, taking into account how and when they buy and at which price points they make the quickest decisions. Having this level of intelligence is improving win rates, stabilizing pricing, and improving gross margins per deal and company-wide profitability.
- Drastically reduces the need for special pricing requests while providing the guardrails needed to prevent rogue discounting across distribution and selling partners. The focus on scaling pricing across a global multichannel selling network that is striving to attain omnichannel levels of customer responsiveness and performance is possible using machine learning and predictive analytics to reduce pricing confusion and errors. Special Pricing Requests (SPRs) can often rob selling and marketing teams of thousands of hours a year. Using machine learning to automate pricing request approvals and rejections, sales operations, marketing, and sales senior management are all freed up to spend more time with customers.
- Guided selling, upsell and cross-sell offers that make sense to the specific prospect, taking into account their budget, decision-making timeframes and preferences. Today, the decisions of which products to offer as part of an upsell or cross-sell strategy are often predicated on a minimal amount of sales data, if any at all. Rarely are the correlations and causal data that drives the sales of one product over another taken into account. Instead, guided selling, upsell and cross-sell strategies are entirely based on what makes the most sense for the company attempting to sell more product. Rarely are the customer’s preferences taken into account. With machine learning and predictive analytics, the customer becomes the center of all selling strategies again. The data they generated from previous selections, transactions and decisions are what determine the products included in upselling and cross-selling strategies. Guided selling strategies become relevant, customers buy more, and they see the connection between their needs and goals with the buying experience. It all starts with greater insight and contextual intelligence of what matters most to them.
- Dynamic pricing that flexes to unique selling scenarios and generates the greatest margin while guiding the highest margin products to be built. Having greater predictive accuracy regarding which pricing strategies make the most sense for each type of customer is the future of CPQ. Having dynamic pricing that can scale across all channels, selling scenarios, direct and indirect selling teams and product configurations is how predictive analytics and machine learning will change selling in the next five years. Look for dynamic pricing to be the most revolutionary aspect of CPQ applications development and platform integration during that time. Pricing and deal optimization are also the catalysts that keep CPQ adoption moving forward, as these two components quantify the value of intelligent selling immediately.
CPQ Is The Foundation Of The Intelligent Cloud Maturity Model
When CEOs, CMOs and CROs (Chief Revenue Officers) are asked to define the most pivotal point when they turned their selling performance around, they all tend to mention the foundational elements of the Intelligent Cloud. Accurately defining the competitive landscape for products and services using descriptive analytics is where the majority of companies begin integrating analytics into their CPQ strategies. The intersection for descriptive analytics and CPQ applications lead to creating predictive analytics workflows that guide pricing, discounts, and advanced deal analysis. As companies mature from multichannel to omnichannel selling, they need data that enables easier collaboration. The model reflects this, with the focus turning to collaboration. At the apex of the model is cognitive analytics, where analytics provide insights into how best to orchestrate selling strategies. The following graphic illustrates the Intelligent Cloud Maturity Model:
There’s a series of revolutionary developments occurring in CPQ today, and this article has provided a glimpse into the most major new ones. The future of CPQ will be marked with greater descriptive, predictive, collaborative and cognitive insights than ever before. Pricing strategies will be finely tuned to the specific decision-making styles of customers when they are most likely to buy. Quotes for the most profitable products will be produced within minutes of a sales call and delivered within the hour. Customer’s time will be respected more than ever before, as will the context in which customers want to buy. The era of intelligent selling is here, forever changing how CPQ applications are used for streamlining and simplifying complex selling strategies.