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Initiate Strategic Business Transformation with AI

Strategic business transformation

Why AI Matters for Your Digital Transformation?

Today’s world is not only dynamic but also highly complex and competitive. The pandemic’s disruptive effects on global markets and buyer-seller relationships compelled many companies to push back on traditional sales methods and move to a digital-first mentality, where eCommerce can play a key role. The aim was clear: to try to deliver more value to customers and to continue to grow effectively. However, due to the complex processes and the often large number of products and customers, leading B2B organizations quickly realized they need a smarter approach to navigate the volatile environment and to achieve desired business outcomes. This is even more crucial now when face-to-face interactions are highly limited and supply chains are completely disrupted.

In this situation, the majority of business executives are facing some important questions around how to respond faster to market shifts. First, how to drive price optimization and higher efficiency in business processes. And secondly, how to meet evolving customer requirements for things such as personalized product offerings and transform buying experiences for the better, especially in eCommerce. As organizations are driven forward by humans, professionals across different business functions often are unable to translate all surrounding events into the right actions and react in a timely manner to new external conditions, without exposing the business to risk. That is why artificial intelligence (AI) technology has become instrumental in driving innovation, competitiveness, and business resilience to market disruptions. It allows core teams in organizations to make quick and informed decisions that are completely data-driven and take into account fluctuating demand, historic and current trends, and even future predictions.

 In this blog, we’ll focus on why AI has become a key enabler of efficiency for businesses that want to adapt successfully to a rapidly changing world. Also, we’ll take a closer look at how it can eliminate “gut feeling” decisions and effectively predict buyer expectations across each and every sales channel, including eCommerce.

Understanding Big Data: Connecting the Dots for the Business

AI enables organizations not only to transform their operations, by reducing manual processes and inconsistent practices but also to translate their “ocean of data” into valuable information. Often these insights are “invisible” to the human eye, but with the help of machine learning (ML) techniques, especially in times of market volatility, they empower business leaders to react swiftly and take proactive measures to remain competitive.

According to Dr. Michael Wu, PROS Chief AI Strategist, data scientists are the ones that hold a crucial role in business transformation, calling ML “The Modern Digital Version of Alchemy.” Similar to turning metal into gold, ML is in the heart of AI because it’s all about distilling raw business data into meaningful and actionable insights. But why is that so hard to do nowadays? Well, big data can be very noisy, because in today’s world organizations are capturing and storing tons of raw business data through digital technology. And when these organizations have a specific issue to solve, their teams end up with huge volumes of data to process and analyze just to retrieve that relevant piece of information related to their specific problem and context. When there’s a huge gap between big data and business needs, how do you find the right insights you are looking for quickly? That’s where machine learning comes into play. Through data science and building models with descriptive, predictive, and prescriptive algorithms, businesses can analyze and extract the right level of information in the form of user-friendly visualizations, to take relevant action against it for the present or the future.

Accurate Predictions for The Future: Detecting Trends and Patterns with AI

We now know that ML is part of AI. Once a business has created a scientific model for a specific process and the team’s decisions, actions, and feedback are completely automated through digital technology, this model continues to be enhanced with new data and adjusted in real-time, to better reflect the new business and market reality. It’s basically a learning loop, where AI constantly improves its performance for the assigned workflow, steering the business toward success.

The AI that automates processes and decision-making within organizations is called “Business AI.” This automation drives overall business efficiency by accelerating processes, reducing costs, and eliminating manual workload for teams. Another key benefit is improved team productivity and the ability to focus on tasks that add more value or are too complex to be fully digitized. According to Dr. Michael Wu, “using business AI will be critical to eCommerce success now because the pandemic has significantly disrupted the demand and diminished margin in many industries.”1 Because by accelerating digital sales workflows, automating product information updates, and improving the market relevance and transparency of prices, organizations increase their chances to convert more buyers in digital channels.

Let us look more closely at different use cases of AI, which businesses can leverage:

  • Customer churn detection: With the help of churn forecasting algorithms, businesses can identify declining buying patterns in customer behavior, while also accounting for seasonality, to deliver more accurate recommendations to sales teams, enabling them to engage with their buyers before it’s too late.
  • Identification of different buying patterns: Using AI, organizations can uncover not only declining, but also gap or inconsistent buying patterns among their customer base. They can use these insights to suggest implementation of relevant buying incentives (% discount, bundles, etc.) that will help drive more sales and increase basket size among specific customer segments.
  • Tailored storefronts to increase visits and incentivize orders: Relying on AI, businesses can display the right seasonal products and services in their eCommerce platforms during the appropriate time of year, aligning with stock levels and digital business goals.
  • Personalized shopping experiences in digital channels: Organizations can capture more wallet share and increase eCommerce adoption and conversions by featuring the right products and personalized cross-sell recommendations to customers as they are shopping online. Using AI to refine these recommendations over time ensures businesses can stay up to date with the latest market trends and the evolving needs of buyers.
  • Finding cross-sell opportunities among existing accounts: AI also helps sales teams uncover more customer value by providing them sales reports with insights on cross-sell opportunities. These allow sales professionals to develop more personalized offers that align with every buyer’s unique product preference and purchase, leading over time to greater customer trust and loyalty.

Making Customer Experiences Smarter and More Personalized Through AI-Commerce

As consumers’ shopping preferences are changing and quickly shifting to digital channels, so are expectations towards sellers. In the ongoing pandemic and market disruption, flexible AI-powered eCommerce platforms like Adobe Commerce are becoming even more instrumental for businesses of all sizes, in both B2B and B2C, trying to maintain market positions across the globe and even achieve further growth. Why so? Because to be relevant to a digital market, where everything is happening in real-time, sellers need to collect and analyze transactional data in a smart way, to deliver instantly more meaningful value to buyers as they are making their product selections and purchases. And when the number of online customers increases exponentially, to scale effectively and continue to serve them with the same ease and relevance.

Customer engagement, conversion and retention in digital channels are now fully dependent on whether a business can provide a frictionless and consistent buying experience. This is the new battleground for modern sellers. And whether it’s “frictionless” is determined by the company’s agility and data-driven personalization capabilities, all of which are a direct result of the power of AI. Let’s look at a few examples how AI-tools can support improved shopping experiences in B2C and B2B.

Markets are different and so are buyers, that’s why “one size does not fit all”. To effectively serve digital touchpoints consumers engage with, B2C retailers need relevant buyer insights on product and service preferences, buying habits, prices etc. in real-time that are then considered in the experiences buyers enjoy. A single AI-powered digital platform allows sellers to manage intelligently their online stores across multiple countries, devices and even for more than one brand. That empowers any type of retailer to serve quickly and in a personalized manner the unique requirements of their shoppers, no matter where they are and how they shop, and ultimately transform them into loyal and frequent buyers without extra efforts or costs.

On the other side, to navigate B2B complexity and drive best-in-class buying experiences in a multi-channel environment, businesses in manufacturing and distribution use advanced self-service customer portals that empower their savvy buyers with seamless navigation and customized product catalogs, transparent dynamic pricing and cross-sell insights, personalized to their evolving demands, as well as simplified ordering workflows that speed up even the most sophisticated purchasing needs.

The Power of AI Pricing Optimization

Recently, Justin Silver, PhD, AI Strategist at PROS, discussed in an article how businesses can leverage AI in several key pricing aspects. First, to unlock the power of their business data and gain a competitive advantage on the market. And secondly, to react more swiftly to market changes, as the cost of commodities is constantly increasing, and thus mitigate the effects of potential inflation risks. According to his analysis, to be successful B2B organizations need to forget about reactive pricing practices and instead rely on AI-infused automated pricing workflows combined with the ability to accurately forecast demand. These two capabilities are quite important to pricing management and optimization processes, ultimately empowering businesses and their pricing teams to weather any looming economic storm and to stay ahead of the rapidly changing environment.

How AI is key to building, managing, and deploying effective pricing strategies:

  • Personalization that follows evolving buyers’ needs: AI provides dynamic price recommendations to sales teams that balance maximized value for businesses with customers’ willingness-to-pay, thus increasing win rates and buyer engagement, and reducing unnecessary negotiations.
  • Alignment of pricing and business strategy: With the power of advanced AI, you can consider not just the willingness-to-pay of each customer, but also focus on the highest probability pricing opportunities and align your pricing outcomes to the preferred business strategy, maximizing margins or revenue across used channels.
  • Pricing designed for digital sales channels growth: AI enables an eCommerce pricing model, accounting for demand elasticity and price elasticity within customer segments, seasonal shifts, and changing competitive situations. Smart technology ensures B2B organizations can drive higher adoption and AI-powered sales through their eCommerce and self-serve channels with precise, differentiated, market-relevant prices.
  • Next-generation adaptive science that follows changing external and internal conditions: By incorporating a feedback learning loop you can be sure AI produces the right optimal prices for every channel in real time, every time. By considering the unique characteristics of each customer you gain and by allowing you to differentiate your sales approach where it matters, AI empowers your business to handle any unique case that comes your way in the future.

Is There a Place for Ethics in AI Technology?

We are now fully aware that AI technology is powerful because it directly impacts people’s lives and business relationships. The extend of that impact is quite significant because AI systems and innovations rely on the use of tons of real-life data – to help consumers find and buy the items they need and similarly, to help businesses achieve intended outcomes. But there are 3 main principles that technology vendors need to take into consideration if they want to be trusted by their customers:

  1. Be responsible in the development of AI-technology, which means to accommodate the values, standards, and norms of society, while avoiding any unintended biases in AI-models to human attributes (like color, race, gender, religion, income, political beliefs, disability, etc.) or any other societal stereotypes, which can negatively impact people’s lives.
  2. Provide transparency on how data is leveraged by the platform by sharing enough information on how a digital business collects and uses customer and usage data in the development of its AI models. Whether it’s to improve the products and services, deliver more personalized experiences, etc.
  3. Take accountability for the outcomes of the AI system’s actions by having the right set of processes in place to monitor and evaluate the performance and possible impact of AI algorithms and models, dataset design and usage, etc. before they are deployed.

Why Is Artificial Intelligence So Important to Businesses? And Where to Next?

AI helps steer B2B companies toward monetization and success by streamlining their commercial operations and decision-making, to deliver the buying and selling experiences their customers and employees expect. Organizations that rely on dynamic AI not only understand buyer expectations better but also by leveraging these smart insights they can execute complex omnichannel strategies and build long-lasting relationships with their customers. In the modern digital era we live in, a consistent and personalized shopping experience means anticipating customers’ needs and harmonizing the right offers dynamically across every touchpoint they interact with.

As artificial intelligence continues to evolve and revolutionize the ways customers buy and businesses sell, implementing the right smart technology can help your organization:

  • Increase efficiency: Significantly improve business efficiency and sales and pricing teams’ productivity.
  • Grow revenue: Increase your revenue by uncovering opportunities for growth.
  • Improve customer experience: Drive a personalized customer experience for your buyers, to compete effectively on the “new battleground” in the business world.

So, once your business implements AI, what’s next? According to Dr. Silver, a key challenge companies face when implementing artificial intelligence technology is how to sustain its adoption in the long term. For successful adoption of AI, time and compliance with the system’s smart recommendations are the two essential factors. The best way for companies to measure their progress and improvements is to rely on key performance indicators (KPIs) that track the benefits of these pricing and sales recommendations on the business over time. The results will help core teams gain trust in AI and continue to apply the recommendations the system is offering them in the future.

To learn more about how PROS can support your business and eCommerce growth, check out our PROS Connector For Real-Time Pricing or learn why pricing is key to digital selling maturity.

1 Dr. Michael Wu, PROS Blog, “Shifting Your eCommerce into High Gear with AI”, June 25, 2020

About the Author

Victoria Dreharova, Product Marketing Manager at PROS, leads the go-to-market strategy for PROS Pricing and eCommerce solutions. Victoria is a marketing professional with strong international B2B background and more than ten years of industry experience in Financial services, IT and Utilities. She is passionate about omnichannel customer experiences and understanding how digital innovations impact business models and drive pricing and selling efficiency.

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