Pricing, the most important lever for revenue and margin growth, is undergoing significant disruption based on advances in analytics and artificial intelligence. While pricing has always been a data-heavy, number-crunching exercise, it is now moving away from simple spreadsheets or tools to Big-Data, analytics-driven algorithms resulting in multiple contextualized prices. “One-size-fits-all” pricing belongs increasingly in the past.

Today, thanks to advanced technologies such as analytics and artificial intelligence, organizations can develop “intelligent pricing”—optimally calculating prices in real time based on multiple customer and market variables, testing price points or entire pricing models and improving them continuously. These new approaches to pricing allow for differentiated strategies with real benefits: more empowered sales (10 to 20 percent improvement), improved margins (up to two percentage points) and increased revenues (5 to 15 percent).1

42%

of consumers say they want companies to use their data securely and responsibly to customize pricing and promotions.

61%

of consumers believe that the use of advanced analytics could result in getting a fairer price.

Many consumers feel they will benefit, as well. According to Accenture research, 42 percent of consumers say they want companies to use their data securely and responsibly to customize pricing and promotions and more than 61 percent believe that the use of advanced analytics could result in getting a fairer price.2 Knowing this, companies can also use intelligent pricing to strengthen trust with customers and, in effect, solidify long-term growth and competitiveness by building into customer attraction and retention strategies.

Pricing gets smarter

Intelligent pricing refers to a tailored approach that determines willingness to pay based on multiple factors such as time of day, location, real-time demand for products and even a customer’s purchasing history. It’s data-driven, not just rules-driven, using algorithms and customer intelligence to deliver instant pricing that is increasingly contextualized or even customized.

An example: When available stock is high, a company might decide to decrease prices, win new customers and boost sales while easing working capital by reducing warehouse use. The next day, a predictive algorithm might alert the company that web traffic for a specific product is high, meriting a slight price increase to boost margins. Both strategies help companies to increase profitability and grow the top line.

Intelligent pricing represents the most sophisticated end of a spectrum of pricing approaches that have evolved over the years—from a mostly manual and generalized set of prices based on static rules to an analytics-based approach where prices can be tailored in real time based on multiple, contextual variables such as demand, competition and customers’ individual willingness to pay—all run by advanced algorithms and artificial intelligence.

A descriptive two-by-two chart showing four different  pricing approaches: rule-based, personalized pricing, dynamic pricing, and intelligent pricing.

Avoiding pitfalls

Several challenges will need to be overcome for companies to effectively adopt intelligent pricing, many of which have to do with technology complexity and skills shortages. In addition, though, companies should anticipate and manage issues involving customer trust. Intuitively, one can certainly see the possibility of trust erosion with intelligent pricing where, from a customer’s perspective, pricing variables are unknown or unclear.

This risk must be addressed head on. Recent Accenture Strategy research into 7,000 companies worldwide found that those that experienced a material decline in stakeholder trust also experienced a corresponding 5.8 percent decrease in revenue growth.3 Risks on this scale are too large for companies to ignore when it comes to their pricing approaches..

One answer is to build trust into your pricing algorithms. All data—which is usually within different silos—could be ingested into machine learning algorithms and used for ongoing price differentiation. For real machine learning, it is also important to have powerful feedback loops in place where, for instance, customer sentiments and behaviors are also fed into the mix.



The journey to intelligent pricing

Properly strategized and implemented, intelligent pricing can increase margins and support growth. To reach that end, here are a few steps to keep in mind:

  1. Build on industry norms. Consider leading practices in your industry, embarking from there to set a new industry standard for pricing anchored in securing and preserving long-term trust with customers.
  2. Think big, start small, scale fast. Use approaches like design thinking workshops to brainstorm an ideal end state for your intelligent pricing strategy. Then put in place a proof of concept (or several) to test ideas for a small product segment or market. Scale successful proofs of concepts across the enterprise as quickly as possible.
  3. Build a business case. Lead with a business case showing the potential revenue and margin growth from intelligent pricing. Also highlight the benefits and risks related to the halo effects on customer relationships. Sales teams, partners and customers will all significantly benefit from intelligent pricing in the short- and long-term.

The new world of pricing

The trend toward real-time, data-driven and more tailored pricing is inescapable. The test for companies will lie in their ability to both master extracting value in the B2C space and also scale it to transactions with their B2B and B2B2C ecosystem partners. The future of intelligent pricing is one that reaches end-to-end across the value chain. When this happens, companies will realize the full spectrum of benefits well beyond steering sales and improving margins and revenues. It will increasingly also be leveraged as a powerhouse to foster enduring customer relationships, ecosystem partnerships and, ultimately, fuel innovation, competitiveness and growth.

1 Accenture Strategy client experience.
2 Accenture, Global Consumer Pulse Research, 2018.
3 Accenture Strategy, The Bottom Line on Trust 2018.

​Johannes Trenka

Managing Director – Accenture Strategy, CEO & Enterprise Strategy​


Dr. Marcus F. Demmelmair

Manager – Accenture Strategy, CEO & Enterprise Strategy​

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