Earlier this week Forrester Research published the latest research on CPQ titled “The Forrester WaveTM Configure-Price-Quote Solutions, Q1 2017“. For this report, Forrester conducted product evaluations using a 36-criteria approach and identified the 11 most significant CPQ vendors from a pool of 50+ active CPQ providers. With this analysis, they determined that:
• Apttus, CallidusCloud and Oracle are the leaders of the pack
• CPQ is being used to streamline sales by connecting front-office and back-office applications
• Intelligence and Extensibility will drive the future of CPQ
The other companies contained within in the report include: Cincom, FPX, IBM, Infor, Model N, PROS, Salesforce and SAP. The stated goal of the report is to show “how each provider measures up” to assist organizations in making the right choice. Some key focus areas of the analysis included: Configuration, Pricing, Quoting, Subscription Management, Channel Support, Platform & Architecture, Intelligence & Analytics, GTM Strategy and Market Presence. To be considered a vendor, you needed to have a complete CPQ solution with front office capabilities, active customers in more than one vertical industry and the ability to support multiple sales models.
Evolving sales organizations require increased extensibility
One question that has always been asked about CPQ is whether it is a front-office or back-office application. This question persists because the answer is both. A modern enterprise CPQ solution should be able to integrate with multiple back-office applications for master data related to products and prices. But, it also must be able to integrate with other components of the Quote-to-Cash process, including multiple CRM and E-Commerce tools. If you are in a subscription-based business, it must also be able to integrate with your assets and support all aspects of renewals and use of IoT data to support a variety of requirements.
The shift from Configurator tools in the back-office to CPQ in front-office began years ago as the usage needs shifted from sales support to field sales users and as the concept of guided selling became more available. But the expansion did not stop there, as the demand for indirect resellers and partners increased. The next evolution includes customer self-service, customer service and automated ordering/ renewals through IoT, intelligent assistants and 2D/3D visualization capabilities. This expansion drives the need for a multi-channel CPQ solution that can support an Omnichannel sales model through pre-built integrations and open APIs.
Another area of extensibility must be the freedom to access the CPQ tool from multiple devices and platforms. True mobility cannot be limited to IOS and Android applications. While this is still an important capability for the direct sales rep, smart technology has expanded from phone/ tablet to the watch and conversational assistants like Siri and #Slack while the mode of communication has expanded from phone and email to include tools like Skype, FB messenger and WhatsApp. If mobility equals anywhere, anytime on any device, then modern mobility must include these tools as well. Consider, for example, the B2B self-service customer that could chat with a digital assistant that supports the buyer during the cart creation process, or can provide guidance relative to volume breaks and available promotions. Or the channel partner that does not have access to your mobile app, because it is connected to your CRM.
The CPQ Market is Expanding and Consolidating
Over the past several years there has been significant M&A activity within the CPQ space, as well as an increased investment from private equity sources. This cash infusion has enabled a rapid expansion of CPQ into new verticals while increasing its horizontal capabilities.
The rationale to invest in a CPQ solution continues to be about getting the right product at the right price to the right customer at the right time. Customers will also benefit from improving their time to market, reducing pricing errors and integrating the complex quote-to-cash process. The difference is that the cloud first approach makes CPQ a viable option to a larger portion of the population while expanded use cases cater to these new vertical markets and companies that did not have complex products to configure, but now have complex deals and pricing strategies that can benefit from a modern CPQ tool. Verticals like High-Tech and Industrial manufacturing were the original consumers of CPQ. More recently increased demand in Communications, Financial Services, Insurance and Media & Entertainment as these organization also can realize a benefit from guided selling, price optimization, dynamic quote generation and integration to CLM tools.
But this expansion is also leading to market consolidation. The increased demand from non-traditional use cases requires an investment from the vendors that not all are prepared to make. This increase depth and breadth of product capabilities is moving CPQ from a point solution to a substantial enterprise application. The key point is that a potential CPQ customer should not evaluate solutions based on what they need today, but consider their evolving go-to-market strategies and the vendor’s ability to scale their support according to the growing needs for CPQ. Today’s CPQ solutions must “enable modern consultative sellers and serve their more demanding customers” across multiple verticals and multiple channel sales models. They must also be able to support persona-based work streams and provide for sales centric capabilities like estimating compensation, rebates and promotions.
“Rules Based CPQ has reached its peak Maturity”
Over time rules engines have evolved into constraints engines and have been enhanced to provide ever increasing capabilities with nested logic and advanced numeric expressions. But as Forrester points out these tools seem to have plateaued and vendors are now “injecting real-time analytics, machine learning, and intelligent recommendations into the sales process”.
Forrester predicts that “2017 will be a pivotal year for intelligent sales apps”. The reality is that the transactional data that an enterprise CPQ solution collects in the normal process of creating and converting quotes creates a target rich environment for the type of real-time intelligence that a machine learning tool can provide. Detailed analysis of win/loss data can result in real-time recommendations for cross-sell/ up-sell, price optimization, quote scoring and several other relevant predictions.
In summary, a modern CPQ solution should not only be able to support all your complex multi-channel needs across multiple platforms and devices, it must provide powerful administrative tools that integrates data from multiple source and must also allow you to start small and grow as your selling strategies mature.