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Practical AI: the Data Science Hierarchy of Needs

Josh Peace — Fri, 24 Mar 2023 14:20:00 +0000

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How to make AI a sustainable revenue generator and not just a shiny (and costly) toy

There is a famous principle in psychology called Maslow’s hierarchy of needs that posits humans require basic fundamental needs be met before they are capable of performing higher order tasks. For instance, food, shelter and social needs must be met before someone can make consistent, stable progress on personal growth and new skills. Shortcuts to self-actualization that build on unstable foundations are neither reliable nor will they progress smoothly.

Similarly data science has a hierarchy of needs whereby continuously-learning production AI systems are only possible and stable when built upon a solid foundation of existing capabilities.

Here I describe that hierarchy of needs, its implications for making profitable data science product suites, and some key takeaways for individual businesses and the evolution of AI in markets.

The hierarchy mountain required depends on the product: analysis identifying a process change to improve business may require only tiers 1–3 for a limited amount of data; an AI customer engagement platform requires tiers 1–6 for a large amount of data. Consider this as the product determining where the peak of the mountain is.

At the risk of mixing metaphors, the data science hierarchy isn’t just a mountain you climb, it’s a mountain you build: higher tiers are built on lower tiers; the lower tiers have more mass (time investment) than do higher tiers and the exact nature of the highest point on the mountain determines what needs to be built below for the system to be stable.

After finishing the mountain that supports a single ML product, the question is “What next?”. It is easy to treat the second, third, and fourth product like the first: decide on the product and make our mountainous path there. But that would be a mistake. In a sane business, the data science products will perform similar calculations or use similar data and those similarities are work that should only be done once.

"if AI is a mountain that needs to be climbed then a suite of AI products are a mountain range that shares the same roots rather than independent mountains"

If AI is a mountain that needs to be climbed then a suite of AI products are a mountain range that shares the same roots rather than independent mountains. Considered that way, each new functionality has value for all future uses (not just the current project).

Our best bets on what will be the second-through-fourth products should inform how earlier products are built, or even which ones are built. An accurate net present value of data science investment comes from a holistic overview of all projects and their interdependencies not just the sum of each project independently. In other words, (e.g.) a long-lived data source has net present value from future products, and awareness of such reusable components changes product priorities.

Therefore expanding our view of the hierarchy of needs has important implications for how a data science ecosystem should evolve and how we should be thinking about making data science products.

take homes

Thinking about a data science ecosystem as a mountain range of products creates some core advice for businesses —

Basic advice for all businesses:

Machine Learning & AI is not the only value in Data Science. Data-based decision making can realize value long before an AI system is built.
Data and infrastructure systems can (and should) support many products, including some that are neither known nor obvious when the system is built. It is smart to build data systems that are robust to several different use cases and provide clear provenance for all data.
Data science capabilities require human expertise just as much as databases, documentation, and computational power. You need to retain your key talent over several projects.
Like any other investment, data science is a balance of upfront costs, probable returns, and how long until those returns are realized. Not all projects should invest equally in reusable infrastructure and data, and data science leadership should have the discipline to make that call.

For a traditional business exploring AI:

In building the mountain, each phase can make returns that support the initial investment. A self-sustaining data science process is a useful discipline for the CEO to enforce (don’t pay for items with uncertain payoff in the distant future), and the DS leadership (don’t be a cost centre, that is the best way to get eliminated in a belt-tightening exercise).
With a clear roadmap, costs can be controlled by only hiring staff needed at that time. Hiring many data scientists and MLOps staff several years before there exists the data infrastructure to support their most specialized skills is a poor use of resources.

For an AI pureplay:

Foundational capabilities are essential to long-term growth. Bootstrapping an AI application on weak datasets and hard-to-scale operational infrastructure is a technical debt that doesn’t just have to be paid off on your first product idea, it will also have to be paid off before making your second idea. (This is not to disparage the value of MVP prototypes — they are the best way to validate what works — it is saying we should not confuse MVP prototypes with a business-ready model.)
Defensible AI business models are built on data. It is borderline impossible to have a model architecture so state-of-the-art that nothing will surpass its capabilities (on similar data inputs). It is comparatively easy to curate data sources and infrastructure that present a sufficiently high barrier to entry to prevent new competitors from entering your market with a meaningfully competitive product.
The cost of good foundations are defrayed across all products and end-users.
- Defraying across many products makes profitable large data investments that no single product would justify, but have excellent ROI on a cohort of products. Disciplined planning should identify these opportunities.
- Defraying across many users makes profitable large data investments that individual customers would not make themselves.

Accepting the above advice as correct, there are significant conclusions about the future of practical AI in business. The economies of scale in specialised data collection suggest that AI SaaS providing services to industry sectors is likely to develop superior returns over individual companies in-housing AI talent save for the largest companies (analogies could be drawn to providers like ARM in chip design). There is also a huge unrealised potential for serial investors to bring data expertise and curated resources into SMEs.

summary

Data science creates value when it enables better decisions. The process of finding the right data and understanding it well enough to make those decisions, or build AI tools to continually produce the right decision, requires building upon a hierarchy of capabilities.

That hierarchy is expensive to build (but bad decisions built on a poor/nonexistent hierarchy are even more expensive), so businesses should tightly control investments in that capability to target projects with the best return.

Considering a product suite and the interdependent roots of the mountain range they require lets you better prioritize projects and where to invest in reusable data + infrastructure.

If you have any questions about practical AI, feel free to reach out to me or the Actifai team.

footnotes

[1] Detailed discussion on this data science hierarchy of needs and its product-focused view.

Jonathan Burley

Head of Data Science - Actifai
03.24.2023

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Actifai Digital: The AI-Powered Future Of Online Broadband and Telecom Sales

Josh Peace — Tue, 24 Jan 2023 21:18:02 +0000

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The shopping experience has changed dramatically in the last decade. Consumers want a more personalized shopping experience, with recommendations that fit their needs and interests, rather than an impersonal list of irrelevant products. And in our modern digital world, they increasingly want to easily subscribe or sign up for your services online.

How can you ensure that your business reflects this shift? By personalizing online customer experiences with your company.

Actifai has been hard at work developing its new Actifai Digital solution to better connect customers with the right products and services when browsing a broadband service provider’s website. Actifai Digital provides better service to customers by tailoring the online shopping experience according to their preferences and needs, increasing the likelihood that they will buy your product or service.

securing the sale — highlighting the importance of customer personalization

To compete in today’s market, you must continue thinking beyond your industry’s status quo — and what has worked for other companies. The industry is seeing an increase in digital transactions, which will only grow as time goes on.

With the rise in digital sales, competitors are easy to search for, and research shows customers are more likely to buy from a brand they know than someone they don’t. Further, when left to make their own product selections, people are more likely to opt for the cheapest or an alternative option that can sometimes prove useless for them, resulting in them thinking less of your service. Therefore, to simultaneously improve customer satisfaction and sell more products and services online, you must personalize your interactions.

But there’s a fine line. If you provide too much assistance, then you run the risk of smothering potential customers. If you offer too little help, customers might leave feeling unsatisfied or confused. Consequently, securing sales in online channels remains difficult.

Thanks to technological advancements, companies are beginning to catch up with consumer demands for personalization. And one innovation has pushed itself to the forefront of this digital revolution: artificial intelligence.

Artificial Intelligence Ensures a Better Customer Experience

Once thought to be something out of a sci-fi movie, artificial intelligence has recently evolved to handle more complex tasks and reduce employee costs and burdens. Already a critical part of most companies’ operations, AI has the potential to make the world better in so many ways — from helping find the best airline ticket to delivering packages faster to changing how cable, media and telecommunication services are discovered and purchased.

The result is increased time for staff to focus on more critical roles — while also reducing costs associated with hiring additional employees to do the same work. Across industries, organizations on the cutting edge are already utilizing AI and machine learning to boost customer retention and satisfaction and increase sales — and the cable, media and telecom industries are no exception.

These sectors are facing a crossroads that could bring them down if they don’t adapt to the reality of the digital age. When faced with steep competition from companies like Netflix and Amazon, which have been able to offer consumers lower-priced and more unique alternatives to cable packages, organizations need solutions to solve their unguided online customer acquisition problem. Leveraging high-tech solutions to address this concern will help service providers stay relevant and provide personalized offers to customers, ultimately reducing the number of abandoned carts and consumers purchasing products that fail to meet their needs.

Customers want to shop online and need helpful digital tools to guide them toward the ideal purchases, yet entirely too many companies fail to deliver systems to effectively support customers in digital channels. Even worse, the benefits of human interaction in live calls do not exist in the digital space and signal an opportunity to utilize AI to deliver the right offer for every customer.

Enter Actifai Digital.

Announcing Actifai Digital

Our new Actifai Digital solution provides machine learning-powered sales support to help recommend the optimal offer and drive revenue.

Customers can take advantage of a personalized experience that reduces friction in the digital sales process and improves customer satisfaction at every touchpoint thanks to the following Actifai Digital offerings:

API-enabled enhancements that offer personalized recommendations and contextual selling points to elevate existing e-commerce experiences.
- End-to-end microsite provides whole front-end usability for providers seeking to expand their online acquisition capabilities, even if they have little or no online presence.
- Rich predictive data that can determine the chances a customer will buy a product by predicting a customer’s price flexibility.
Engaging discovery flow helps customers discover their ideal offer and increase the likelihood they will subscribe by helping them identify their needs without increasing cart abandonments.
Machine learning and AI that combines over 1 million proprietary outcomes from previous sales engagements and robust predictive data to deliver an optimized offer aligned with a customer’s actual situation.

Leveraging AI and machine learning algorithms, Actifai Digital analyzes data from live sales interactions, identifies potential issues and suggests solutions to improve performance.

Data shows that customers are more likely to buy when presented with more targeted offers. Plus, research reveals that 80% of telecom customers are more likely to make a purchase when offered a personalized experience. Positioning an offer to show precise alignment with the customer’s actual situation can result in more qualified leads and more opportunities for success with increased revenue for your business.

Actifai’s platform, leveraged by seven providers, including three of North America’s 10 largest cable operators, helps providers to sell more products and services by improving the self-service elements of their websites, apps and other sales channels. With Actifai, service providers have seen ARPU increase by as much as 14% and the average 60-month customer lifetime value by up to 30%. Providers utilizing Actifai have also doubled their sell-through rate for add-on products.

By delivering dynamic offers integrated directly into web sales flows and presenting them to online shoppers side by side with their unique offers, the innovative Actifai Digital platform is a one-size solution for any service provider, big or small.

from small to large companies: the AI-powered future of digital sales

The digital revolution is creating a new world for small businesses. The number of small cable, media and telecommunications companies in the U.S. and around the world is increasing. This growth comes with an increased need for solutions to help these organizations succeed, and small service providers stand to benefit greatly from a digital microsite solution.

Call centers can be expensive, and sometimes a business doesn’t have any online presence. When quick and accurate serviceability is a must to capture new subscriber opportunities, these companies are at a disadvantage unless they can fill their gaps in service.

The AI-powered future of digital sales with Actifai means that smaller organizations can compete with larger companies by offering a better customer experience using AI. Cost-effective, scalable and easy to implement, Actifai Digital helps boost sales, increase customer satisfaction and reduce customer churn.

On the other hand, large cable, media and telecommunications companies can use Actifai Digital’s APIs to bolster customer background with industry-leading data discovery, engage their customers in purchasing with a tailored discovery flow and boost ARPU by providing a single optimized offer to each customer. This helps scale up their digital marketing initiatives and create an integrated digital experience across all products and services, which is essential for companies that want to attract new customers and expand their business reach.

With Actifai Digital, the Future of Digital Sales is Bright

A better way to shop for cable and internet services, our innovative Actifai Digital platform streamlines the digital sales process for consumers and companies. By helping organizations improve sales productivity while creating a more seamless customer experience, the unique platform allows any size business to grow its operations and increase its revenue with more targeted customer offers. The future of digital sales is powered by AI and machine learning.

If you’re looking to move consumers from browsing to buying, see what Actifai Digital can do for you.

Actifai

01.24.2023

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Actifai Serviceability Module: how actifai solves the address check challenge for cable and telecom providers

Josh Peace — Fri, 15 Oct 2021 15:10:09 +0000

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