Everywhere you look, proponents of Artificial Intelligence (AI) tout its vast application potential for optimizing business across every industry, from agriculture to utilities. Some even predict AI’s key role in forming new scientific advancements that will lead to the creation of entirely new industries.
A majority of organizations lag behind those futuristic headlines however. They wonder if and how AI is really for them. To gain additional perspective, I recently sat down with Nolwenn Godard, Director of Pricing Product at PayPal and a Vendavo customer to discuss AI, how it may affect pricing, and its possible impact on an organization’s overall commitment to commercial excellence.
I started with a question about the pricing process, and Nolwenn broke her answer down into two parts, optimization, and execution.
Q: How might AI impact the pricing process?
A: Price segmentation/optimization
Customer data is everywhere, obtained from social media, the internet of things, ecommerce purchases, location based applications, and more. AI will be essential to digesting this information, and help create and capture new value. Machine Learning and predictive analytics (on customer wants, behaviors, price sensitivity) will allow for precise customer segmentation, and mass personalization at scale. Customers insights will be leveraged to increase the value of products, services, and experiences provided to customers (e.g. convenience of anticipatory shipping). It is an opportunity for value-based pricing, monetizing innovation, innovative pricing models and intelligent price optimization. However, we can anticipate some price pressure from increased price transparency and negotiating power. In that context, companies will need to study and outsmart their competition. Pricing will need to account for that goal.
A: Price execution
Many companies seek optimization that helps reduce their price-to-contract process, or adjust pricing in near real time. AI can help with these goals. AI provides the ability to optimize operations and in particular, price execution. By combining predictive – and prescriptive – analytics, and the data-mining capabilities of AI with the automation capabilities of pricing and contracting software, AI can:
- provide recommendations on where to focus to increase deals;
- increase the forecast accuracy of sales;
- provide automated price guidance;
- strengthen sales pitches;
- increase the efficiency of contract creation, management and compliance;
- help detect and prevent churn; and,
- help identify issues and opportunities invisible to the human eye.
Next, I turned to the topic of what customers go through as they engage with companies, and asked Nolwenn how those experiences impact the commercial process.
Q: How can AI enhance customer experience?
A: Companies have new tools when working toward enhancing their customer experience. They can leverage insights obtained from multi integrated systems (like pricing software, customer relationship management tools) and external data sets.
AI can help companies speak intelligently to their customers, offer them relevant and personalized products and services, increased human attention (freed up from routine operations), and enhanced customer service with media intelligence such as social media text mining to understand customer pain points before they interact with the company. The next level of intelligence will probably allow customers to resolve many of their issues directly interacting with more advanced chat bots (able to talk, see, respond or proactively provide recommendations). Finally, AI will help address the factors of customers’ dissatisfaction before they churn.
We then turned to a concern held by many knowledge workers and managers: what’s the outlook for pricers as AI use increases?
Q: How will AI impact pricing professionals?
A: As with many industries, AI and automation have the potential to change the nature of how pricing professionals will work. They will be able to shift their focus to highly analytical and creative tasks while still being assisted, ‘augmented’, by AI for these activities. Monitoring and alerts, automated data driven reporting, user-friendly visual analysis, actionable intelligence along with the easier use of data will provide simpler, more confident decision-making. Pricing professionals will need to develop the technical literacy to understand Big Data and use AI tools. They will need to be responsive to new data while also inventive to leverage the information for pricing (e.g. proposing business models changes based on new data or new capabilities, like shifting from selling aircraft engines to selling engine uptime and insights on aircraft, in case of technical progress of engine uptime and sensors).
For our last topic, I asked Nolwenn about her thoughts for companies as they consider adoption of AI.
Q: What challenges exist for AI adoption?
A: First and foremost, AI is still emerging. Its adoption is likely to increase as more AI use cases are created and more complex AI becomes available. Technologies like deep learning, mature Natural Language Processing (NLP) and real time handling of larger data sets continue to evolve and provide ever-more-advanced solutions, with an increased human experience of AI.
Second, there is currently a lack of talent to develop the actual AI/ML compared to the needs. This is a skills and workforce gap that will need to be closed for further advancements and maturity of these technologies.
Finally, AI applications are only as good as the quality of data behind them and the ability to gather clean data for AI systems is a challenge. Data privacy regulations may make collecting personal data more complex, particularly in light of the General Data Protection Regulation (GDPR) that is coming into effect in 2018 in Europe.
AI is already enabling organizations of all types to rethink the way they do business. Remember, how and where you shift your focus with the support of AI should be for the sake of commercial excellence.