In B2B sales, it’s a harsh reality: Buyers are more independent than ever. Before making a purchase, they research products and services on their own, searching online and asking their peers for advice. By the time they actually reach out to a sales rep, 60% of customers already have a short list of vendors.
When a customer is ready to buy, the last thing you want is to keep them waiting for a quote. If a rep spends days or weeks poring through pricing and product spreadsheets, customers will quickly lose patience and you’ll lose them forever.
So what’s a company to do?
Benefits of CPQ
Here is where configure, price, quote software can make a difference. By automating their CPQ processes, companies can empower their sales reps to produce fast, accurate quotes. They can close deals quickly at the optimal price, and customers get the experience they expect.
But if you’re shopping for a CPQ solution, how do you know what to look for? How do you choose the right product for your business?
Buying a CPQ? 5 things you should know
During a recent SAP webinar with guest Forrester, the research firm offered insight based on its survey of 36 companies that use CPQ. Forrester boiled the results down to five top considerations companies should keep in mind when choosing a CPQ solution.
1. Support for adjunct technologies
Most every CPQ vendor claims deep integration with CRM and ERP applications, but customers need to look for integration with other types of applications, according to the webinar’s guest speaker, Daniel Hong, VP and research director at Forrester.
In order to ensure quote efficiency, CPQ should integrate with contract lifecycle management (CLM), commerce, and pricing management tools as well as reporting and dashboard tools, he said.
“The reality today is that customers can’t afford to evaluate CPQ in a vacuum,” Hong said. Companies need to look for holistic capabilities in the CPQ suite or ecosystem, he added.
Many companies need a CPQ that fits their specific needs of their industry and CPQ end users, Hong said.
For example, salespeople at a manufacturing company may put together configurations with thousands of variables; they need an interface that helps them keep track of everything. Engineers also need a workflow that allows them to contribute easily to the configuration data.
A telco or airline with extreme pricing volatility needs dynamic pricing capability in order to support the buying habits in their industry, Hong said.
3. AI-driven pricing optimization
Advancements in artificial intelligence have enabled CPQ vendors to add the capability to provide machine learning-generated recommendations for pricing and discounts. AI-driven pricing optimization no longer requires a data scientist to implement.
Companies with complex products, high-transaction volumes and price-sensitive buyers get the most value from AI-optimized pricing, he said.
Hong advises buyers to look closely at how vendors use AI to generate discount recommendations, which can impact other capabilities such as AI-driven upsell and cross-sell recommendations. AI-driven pricing optimization is a good representative set of capabilities that can foreshadow a vendor’s chops in AI and machine learning.
“Not all AI are created equal,” he said.
4. Ability to provide a B2C experience
With more than half of B2B buyers preferring to get their information online instead of working with a sales rep, a CPQ solution should support the burgeoning B2C experience with self-service capabilities.
More and more B2B buyers are shifting towards self service, preferring to configure products and receive discount recommendations online, Hong said. CPQ products need to account for the Amazon effect.
5. Innovation and support for future B2B buyer needs
When shopping for a CPQ solution, companies should look beyond solving immediate business problems, Hong advised.
New technologies such as the Internet of Things are leading companies to develop new subscription-based business models. Buyers should consider whether the CPQ can handle usage-based, value-based, or outcome-based models, and manage renewals, upsells, and downgrades, he said.
Overall, organizations evaluating CPQ products should focus on business outcomes, Hong said. Look at the CPQ’s ability to shorten the deal cycle, increase deal conversion, and improve customer experience.
Looking forward, Hong said he expects CPQ technology will evolve to take the application of machine learning to new levels with bigger and better data sets that increase scale, accuracy, and speed.