Thursday, February 22, 2024

"Network as an Experience?"

Connectivity service providers these days often use words such as “experience” or “personalization” or “seamless integration” or “user defined” or “advanced features” when describing the value of their products. 


That should not come as a surprise. Most industries and firms try to do the same thing with their own products. 


But the use of such phrases does raise some logical issues. To the extent that the emphasis is on “experience,” how far can that focus go? We might all agree the focus on “experience” or “personalization” is a helpful way to sell existing products to existing customers. 


But can such emphasis go further, perhaps adding new roles in value chains that did not exist before? That is not an easy question to answer. Selling anything “as a service” rather than “as a product” can represent a new role in a value chain. 


The classic old telco example is voice services, which were purchased “as a service” by businesses and consumers, while sellers of business phone systems essentially sold a “product” that allowed customers to create their own voice services. 


In the internet era, hyperscale “computing as a service” suppliers essentially sell a service that customers once purchased as a product (computing machines). 


It is not so clear whether connectivity service providers can leverage “personalization” or “experience” in similar ways to create new roles in the value chain. That is a different matter from reshaping products in ways that are more “user friendly” or “personalized.” 


With the caveat that the phrase “network as an experience” or “network as a service” can be defined, they imply that a tangible product (internet access, for example) can be refashioned as an “intangible” product. 


The general shift is from something that can be measured to something which is difficult to measure; something with basic value or attributes  to something with enhanced value and attributes; almost always implying also a shift from “commodity” to “not a commodity” status. 


But there are at least a few ways the phrase “network as an experience or service” could mark a departure. In the past, “connectivity” services have been physically limited: legally authorized only in certain geographies by law, whether that is a city; a state or province or a nation. 


The rise of all forms of all sorts of exchanges and marketplaces for retailing, for example, illustrate a different model. As e-tailers such as Amazon or Alibaba frequently or mostly enable transactions between buyers and sellers, and do not actually “own” the merchandise sold, so at least some connectivity services might be envisioned as products sold by firms that are facilitators, platforms or marketplaces, not owners of connectivity assets. 


Think of firms that allow buyers and sellers to conduct transactions for various types of services, but without actual ownership of the inventory. Where a traditional connectivity services provider makes its money selling services on networks it owns, a platform or marketplace might make its money in the form of commissions on services sold that use the exchange. 


So even if all connectivity networks “sell services,” an exchange might plausibly be said to “facilitate those transactions.” Network-owning connectivity providers make their money selling connections and bandwidth; marketplaces make their money hosting the transaction platform and earning a commission on completed transactions. 


The major point is that much of the marketing spin around personalization or experience, while meaningful as a way of enhancing the value of existing products, sold to existing types of customers, with existing types of assets, is less apt to create new roles in value chains. 


On the other hand, the business model for a marketplace or platform is different. Airbnb does not “own” the properties that are rented by guests on its platform. Uber does not own the vehicles driven by its drivers. 


In fact, we might not be able to find many industries that do not attempt to use internet-based technologies to personalize and customize their products and services for customers, though the trend seems most advanced for intangible products that--by definition--exist only in performance. 


Tangible products are physical objects whose value can be be embedded in their physical characteristics, materials and functionality. They have “specifications,” for example. 


The performance of tangible products can often be demonstrated beforehand through reviews, testing, or even simple observation, so tangible products allow for some degree of pre-purchase evaluation, reducing reliance solely on "performance" after purchase.


Intangible products cannot easily be evaluated that way, as “quality” exists only in “performance” or “experience” of the product. Intangible products like legal advice, financial advice, or music performances derive their value entirely from their execution or delivery. One cannot fully know their worth until you experience them.


The "quality" of intangible products is often subjective and nuanced, whereas the performance of an auto, a computer or a piece of sports equipment can be quantified more easily. 


So perception matters, especially in the pre-purchase period. Basically, one often has to experience an intangible product directly to understand its value.


Intangibles require trust and reputation: Due to the "performance only" nature of intangibles, consumers rely heavily on trust and reputation when making buying decisions. Word-of-mouth recommendations, qualifications, and past performance become crucial factors.


Intangibles require higher engagement: Since the value of intangibles unfolds during the performance, active engagement from the consumer is often crucial. Active participation in legal consultations, financial planning sessions, or music performances can enhance the perceived value.

Marketing needs to focus on outcomes: When marketing intangibles, emphasizing the potential outcomes and benefits of the performance is more critical than showcasing inherent features.


Industry

Personalization and Customization Examples

Benefits for Customers

Benefits for Businesses

Retail:

Product recommendations based on browsing history and purchase data.   Subscription boxes with curated products based on preferences.   Personalized discounts and promotions.

More relevant product suggestions, leading to higher satisfaction and purchase likelihood.   Discover new products they might enjoy.   Feel valued and understood by the brand.

Increased customer engagement and loyalty.   Improved conversion rates and sales.   Valuable customer data for future marketing and product development.

Finance:

Personalized financial advice based on individual goals and risk tolerance.   Customized loan offers and credit cards.   Budgeting and savings tools tailored to income and spending habits.

Better financial decisions and planning.   Feel more in control of their finances.   Access to products and services that meet their specific needs.

Deeper customer relationships and trust.   Reduced risk of defaults and churn.   Cross selling opportunities based on customer data.

Healthcare:

Personalized treatment plans based on medical history and genetic data.   Telehealth consultations with doctors who specialize in specific conditions.   Wearable devices and apps that track health metrics and offer personalized coaching.

More effective and targeted treatments.   Improved health outcomes and quality of life.   Convenient and accessible healthcare options.

Improved patient engagement and adherence to treatment plans.   Reduced healthcare costs.   Development of new personalized medicine solutions.

Travel and Hospitality:

Personalized travel recommendations based on interests and budget.   Dynamic hotel pricing based on demand and customer preferences.   Customized itineraries and experiences.

Discover new destinations and travel options they might enjoy.   Feel like their trip is planned specifically for them.   More memorable and enjoyable travel experience.

Increased bookings and revenue.   Improved customer satisfaction and loyalty.   Ability to cater to different customer segments with targeted offers.

Education:

Adaptive learning platforms that adjust difficulty and content based on student progress.   Personalized learning paths and recommendations.   Online courses and tutoring tailored to individual needs and learning styles.

More effective and engaging learning experience.   Achieve learning goals faster and easier.   Feel more motivated and supported in their education.

Improved student outcomes and completion rates.   Increased student satisfaction and engagement.   Development of new and innovative learning solutions.

Entertainment:

Streaming services with personalized recommendations based on watch history.   Music platforms that curate playlists based on listening habits.   Video games with customizable characters and storylines.

Discover new content they might enjoy.   Feel like the entertainment is chosen specifically for them.   More engaging and immersive experience.

Increased user engagement and retention.   Valuable data on customer preferences for content development.   Ability to offer targeted advertising and promotions.


                      


Walmart Buys Vizio to Compete with Roku, Other Ad Giants

The announced acquisition of TV manufacturer Vizio by Walmart will marry Walmart's streaming content with a key appliance supplier, boosting opportunities to create advertising revenue. 


The acquisition would give Walmart a stronger foothold in the smart TV market through Vizio's SmartCast platform, boosting Walmart's position in the battle against other major retailers, ranging from Amazon to Target and Costco. 


But the deal also makes Walmart a bigger player in the advertising market, positioning the firm to compete to some extent with Amazon, Google and Meta for digital ad spending. 

By some estimates, Amazon controlled 75 percent of the $45.15 billion U.S. retail media ad market in 2023. Of course, the total U.S. digital ad market is larger. 


U.S. Digital Advertising Estimates, in Billion USD


2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

Statista

90.08

114.70

139.00

168.70

224.20

243.90

271.20

298.40

325.00

350.90

376.50

402.00

Cowen and Company





183.40

221.00







GroupM

73.39

90.99

107.10

121.90

157.70

189.10

205.70

229.80

243.30

266.30



Magna




136.00

179.00








PricewaterhouseCoopers (PwC)

88.30

107.50

124.60

139.80

189.30








Winterberry Group


127.70

152.90

176.70

240.40









Other estimates of retailer advertising suggest a smaller market. The IAB, for example, estimates current retailer revenues at lower levels. But most estimates suggest Walmart shows the fastest growth in the category.


In 2023, for example, Walmart digital ad revenues grew 42 percent. Amazon almost certainly posted the greatest amount of net new ad revenues in 2023 at $5.5 billion.


Year

Estimated Annual U.S. Retailer Advertising Revenue (USD Billion)

Growth Rate (%)

2023

10.0

N/A

2024

11.5

15%

2025

13.3

15.6%

2026

15.4

16%

2027

17.8

15.6%

2028

20.4

14.6%

2029

23.3

14.2%

2030

26.5

13.8%


But retail leads digital advertising, accounting for perhaps 28 percent of all such advertising in 2023, followed by consumer packaged goods at about 15 percent of total and financial services at about 11 percent of total.  


Wednesday, February 21, 2024

Google Releases Open Source Gemma Models

Google has gone open source with two Gemma family lightweight generative artificial intelligence models built from the same research and technology used to create the Gemini models. Gemma 2B and Gemma 7B also come with pre-trained and instruction-tuned variants. 


The pre-trained and instruction-tuned Gemma models can run on laptop, workstation, or Google Cloud. 


That move follows Meta’s open sourcing of its LLaMA (Large Language Model Meta AI) in 2023 for approved researchers and organizations. In February 2024 Meta released a commercial version of LLaMA 2, making it freely available for both commercial and non-commercial use. This includes access to model weights and starting code for pre-trained and fine-tuning purposes, but not detail on the full training data used to create the model. 


Google compares Gemma to LLaMA.


source: Google Blog 


Meta also contributes to the OPT (Open Pre-training Transformer) open source language model.


As one might expect, controversy exists over the release of open source models, as some argue this will encourage use by bad actors generating harmful content, spreading misinformation, or launching cyberattacks.


Supporters argue that open source AI provides transparency and reproducibility, enabling researchers and developers to understand how the models work, identify potential biases, and contribute to their improvement.


And some arguments might support either point of view. On one hand, potential bad actors might not have access to the resources to create or train their own models. So open source might enable them. 


On the other hand, the same resource limitations also inhibit use by individuals and firms who might be able to create useful capabilities. 


Some might note that all technology can be used for good or evil.


Tuesday, February 20, 2024

Google Launches Lumiere for Text To Video


Some observers say Google is "behind" in the AI "race." I'm not among those who believe the present state of development--who is "in the lead"--is at all related to what happens in the future. 

The early leaders in the hobbyist personal computer space did not emerge as leaders of the mass market business. 

The early leaders in music streaming did not become the present leaders in that area. 

MySpace, though early in the social media space, did not emerge as a leader in the more-mature market that followed. 

That is not to say it cannot happen that an early pioneer emerges as the leader in the fully-commercial markets that develop over time. Amazon and Netflix are good examples. 

Still, early success does not typically guarantee leadership in the big markets to follow. 

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