- 7 ways to use AI for effective business process optimization
Artificial intelligence provides a myriad of opportunities for businesses to optimize their processes. Improving the customer experience through deep personalization is known, but it also drives commercial performance in generating revenue, boosting cost savings, and delivering operational efficiencies.
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We’ve all experienced how Artificial Intelligence provides intelligent 1:1 digital experiences.
Today’s leading AI-driven profiling and decisioning solutions are built on the pillar of predictive user-profiles, processed in real-time by machine learning technologies. Processing huge swathes of customer data and engagement signals allow us to create experiences that deliver customers the most relevant content and offers.
It is essential to recognize that once your business has the ability to profile – and understand – your users in real-time, there are countless additional opportunities to solve other commercial challenges. Tech should be more than a one-trick pony. AI-driven profiling and decisioning must also contribute to solving concrete business problems. This technology has the capability to help companies optimize business processes, ultimately improving revenue and being more efficient.
McKinsey found that while general AI adoption has been quite stagnant since 2018, it’s the growing number of varied AI capabilities organizations deploy which is having a profound impact on business, with usage up 100% from 2018 to 2022.
In this post, we explore the way business can use AI to optimize processes for revenue generation, tackle cost and operational efficiencies.
Optimization that improves revenue and business performance
Intelligent personalization is able to target individuals on a 1:1 basis – even those who are not logged in and interact online anonymously. By harnessing the power of artificial intelligence-driven profiling and decisioning, digital engagements can be optimized to drive revenue generation, manage costs and improve operational efficiencies in a number of ways. The following examples explain typical use cases of BD4 clients in the airline, travel and retail space.
Each requires a deep real-time knowledge of your entire audience, with intelligent 1:1 user profiles tied to machine learning algorithms that create bespoke, highly responsive, intuitive customer journeys. Historical CRM data and rules based segmentation approaches are not sufficient to generate the needed user insights, especially not for anonymous users and today’s fast changing demand patterns.
1. Margin optimization
Alongside the deep understanding of individual users on your site, AI-driven profiles are paired with equally thorough product profiles to find the ‘perfect match’ for shoppers.
Companies seeking to optimize their margins steer users towards the most relevant products that have a superior profit margin at the same time – while avoiding presenting products that would drive churn due to unmatched requirements. Doing this at scale and in real-time is only possible with the power of AI-driven profiling and decisioning technology.
Find out how BD4’s AI-powered personalization solution supported easyJet holidays by showing real customer-centricity. The company was able to increase their revenue by 5.23%, representing a ROI of more than 600% from the AI investment.
2. Monetization of digital real estate
A significant and unexploited revenue travel and retail businesses have is monetizing non-customers. Earning profit from digital traffic should not be limited just to those users who buy from you – learning to let go of those who are predicted to not convert in your shop may seem counterintuitive but is, in fact, a smart business practice.
With the right technology in place, you can identify the right user to let go – those who are unlikely to buy from you – and redirect them to more suitable shopping experiences, acting as a paid advertiser or referral partner. The concept of commercially targeting specific audiences is omnipresent, but understanding regrettable versus un-regrettable churn can help you develop an additional revenue stream.
Read our ‘Learn to let go’ eGuide for more information on how to best market and monetize your website’s digital real estate.
3. Building an effective loyalty program
Effective loyalty programs remain one of the ‘holy grails’ for marketers: first-party data is increasingly valued and being able to utilize information in a way that helps earn loyalty through “corporate transparency and honesty” is key to building a robust loyalty program.
A major lever to boosting business efficiencies and optimizing processes around loyalty programs and reward schemes also relies on 1:1 user profiling. Knowing your customers is always key and understanding what they want and need by digitally listening to them is possible – with the right technology that captures the required data points and interacts intelligently in real-time with known and unknown digital users.
By presenting the most relevant benefits of your program to loyalty participants in the right context, at the right moment, with the right message is the ideal approach of optimizing customer engagement as part of your business processes.
4. Incentive and discount optimization
Understanding user intent is vital for your business process optimization and performance, when it comes to discounting and providing incentives. Instead of that, a blanket-approach is used by many companies, presenting the same flat rate of discount or identical value-adds to every user. This approach may drive conversions but can ultimately hurt your profit line by facilitating discounted bookings to customers who would have booked at the normal rate or even higher-graded offers.
Avoiding unnecessary discounting ensures a more effective allocation of incentive and rewards budgets, it increases your revenue per user by between 3% and 6%, and minimizes churn.
Discover how we helped an international airline increase revenue with personally targeted incentives, saving more than $1M USD over 10 months compared to a more traditional distribution of vouchers.
5. Optimize transaction costs
At different times throughout their shopping journey, users may be happy with less accurate results for a faster shopping experience and therefore benefit from faster (and less costly) cached pricing results rather than complex live pricing requests. Instead of defined products the customer may seek broader inspiration enabling the business to be more cost effective and responsive by using cached frontend databases.
This is again where understanding visitor intent can be used effectively to improve business performance. Where companies experience high costs in collecting or sourcing fresh data and information (particularly having to work or go through third-parties to access this data at a cost), or the process suffers a time lag – AI profiling intent can be used to substantially reduce the impact on the business.
6. Improve the optimization of marketing
AI-driven profiling and decisioning assists with target remarketing, sharing messages primarily with users who are predicted to be potential bookers or big ticket buyers on your platform. This helps commercial teams avoid waste within marketing budgets – of both time and money – by reducing promotions to users who will not buy. Today you are able to know which share of your marketing budget would potentially be wasted.
By optimizing processes around marketing efforts and audience targeting, together with a well-developed strategy, your business can drive direct and cost effective sales results.
Discover the difference between Segmentation and Personalization to turbo charge your marketing campaigns.
7. Drive operational excellence
By applying mechanisms throughout the customer journey designed to predict demand, AI can understand purchase behaviors and establish ordering requirements to ensure your store is always stocked, particularly of the right products. AI profiling can also detect specific customer-types so you can better manage their brand experience.
Knowing in advance which users have a high-return or cancelation ratio is one way user profiling can impact operational efficiency. For example, understanding what clothes a user is likely to buy, and what he returns, enables retailers to recommend the best color, size or cut to avoid choice orders of multiple items.
Also promotions and mailings can be adjusted to steer users away from liked but individually non matched products. Some users are driven away by their expectations of a product. By being unbiased and insight-driven through the analysis of hundreds of different data points, the AI is able to understand what users want, before they even know it.
How BD4 can help with your business process optimization
At BD4, we harness technology to provide our clients with a human touch shopping experience. Digitally emphatic personalization is no longer a future potential for companies operating in the digital space; it is a capability that is available and simply can (or must) be used to optimize conversion and improve your business.
Understanding the attributes of both users and products in their current context allows travel and retail companies to serve the most relevant content (whether that be offers, images, product listings, text descriptions or more) and services (from call-backs to loyalty schemes and incentives) for each individual user, prioritizing engagement and relevance at all times.
Furthermore, artificial intelligence can assist humans with some tasks, freeing up teams to focus on more strategic tasks. It can also do things humans simply can’t – especially when it comes to providing 1:1 real-time personalization at the scale of your entire audience. Analyzing users on an individual basis is where the technology shines, providing numerous ways for companies to optimize their business processes and boost customer engagement and sales.
Discover more about how BD4 can help your business through AI-driven profiling and decisioning – even engaging with anonymous users – by getting in touch with our team.Contact us