If you recognize the potential that artificial intelligence (AI) can bring to your business but don’t know where to start, the impact of AI on price optimization, personalization and sales efficiency will be the most impactful types of technology investments in 2022, says Michael. Wu, PhD, Chief AI Strategist for PROS Holdings.
If your business knows AI can deliver value, but doesn’t know how to start applying it to your situation, Wu is a great place to start for you. After all, if you want to maximize your profits, you have to reduce your costs or increase your income and when it comes to prices, you no longer need to roll the dice; instead, you can apply rich AI experience to your own data to monetize more effectively and maximize your profits.
ADVANTAGES is a cloud-based software company that drives the transition to modern commerce by helping businesses create personalized and seamless shopping experiences for their customers. PROS applies machine learning to the science of dynamic pricing and enables companies to price, configure and sell their products in an omnichannel environment with speed, accuracy and consistency.
Michael wu, its chief AI strategist, is one of the world’s leading authorities on AI, machine learning (ML), data science and behavioral economics. He explains, âAI can ingest large sets of data to gain a complete understanding of the market landscape, the competitive environment, and buyers’ willingness to pay. “
âAI has the ability to take into account a large number of attributes in the input data and make a truly optimal price recommendation across multiple dimensions,â Wu said. âWhen AI is trained in it Using user behavior data, it acquires a holistic understanding of user preferences and is able to recommend content, products or services optimized for the individual. The use of AI also supports the ” sales efficiency, because AI typically automates mundane, repetitive, and error-prone tasks that often take a long time for humans to complete.Use of AI can automate these tasks with speed, scalability, and precision, leading to an acceleration of slow processes in long sales cycles and therefore to greater efficiency. â
In fact, not only is price optimization something you can apply to your data right now, but it will be the most impactful type of technology investment in 2022, Wu says.
“Price optimization, personalization and sales efficiency tools such as configuration, price, quote (CPQ) have direct impacts on revenue, customer experience (CX) and operational efficiency respectively, “he said.
âWhen properly adopted, these solutions can add value and have a direct impact very quickly – that is, they have a very fast time to value. If the sales team adopts the price recommendation of price optimization solutions, the impact on revenue and margin is immediate. When a personalization tool is adopted by consumers, users can immediately feel the improvement in the customer experience. And when the sales efficiency tools are adopted, the sales team will immediately operate more efficiently, âWu said.
Of course, while AI can process volumes of data in bulk, there are other things to consider. One of them is to alleviate any sort of bias and leverage aspects of “human intelligence” to keep your AI on track.
âBias in AI and ML models typically occurs when the data used to train AI is biased,â Wu said. âIf we can ‘fix’ the training data, we can solve the majority of problems. bias. Human analysts should review the training data and analyze the entire population of training data to identify potential bias in any of the protected attributes, such as race or gender, before the data becomes available. ‘training are not used to train the AI. “
âExamining a small sample of the training data will not reveal the inherent biases, as they are not observable on an individual basis. After examining the entire data population, if any biases occur, analysts should work with data engineers to rethink an unbiased training dataset for AI training. Since AI learns and is often retrained periodically, these analytics reports serve as a monitoring system to ensure training data stays within the pre-defined threshold of impartiality, âWu said.
In addition, companies must adhere to ethical standards and responsibility when it comes to AI.
âIt is absolutely crucial to uphold the ethical standard and the responsibility of using AI, as it builds trust between users and business leaders,â Wu said.
âWhile AI can generate tremendous value in their respective ROI – like improved margins, CX, and sales efficiency – it will only do so if humans embrace and use these AI tools. . And humans will only adopt these tools when they feel they can trust them. Without trust, humans will not use these tools, and there will be no perceived return on investment or business impact, âWu explained.
Along with ethics and eliminating bias, it’s also important to have the right teams of people who will uphold the ethical values ââof AI of end-to-end integration.
“Deploying teams dedicated to upholding ethical standards and the responsible use of AI will help build trust, combat fear of AI, and provide more transparency on how AI takes its decisions, âWu said.
âUltimately, the right team of people will ensure that the AI âânot only performs as intended, but also mitigates any potential negative side effects, which will ultimately build the trust of the intended users in the AI,â he said. he explained.
Business and IT leaders around the world know there is an opportunity to unlock business value by harnessing the power of AI. If your business is still looking for a way to start, price optimization is a great place to start. Wu has some advice on how you can get started.
âThe adoption of AI is a very long and multi-year journey. I developed a vendor-independent, use-case, six-step AI adoption maturity model that describes this process, âhe said.
âDepending on the maturity level of the business, they will have to focus on something different. For those new to this adventure who haven’t embarked on this adventure, I would recommend that they start collecting data on their business operations. “
âAI is essentially powered by data, so having big data about their business captured and stored will allow those businesses to have the raw materials needed to power AI, to use as training data for train AI Due to the recent pandemic, most organizations have accelerated their digital transformation.
âThis is good news,â Wu said, âbecause this is precisely the first step in the AI ââadoption maturity journey, which involves the digitalization of business processes.â