All the President's men
When the world's second richest man, Meta's Zuckerberg, was displeased with the revelations of an ex-employee, Sarah Wynn-Williams, on unsavoury behaviour inside the company, he tried to prevent Wynn-Williams' tell-all book, Careless People from being sold in the US (it had already appeared in the UK).
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Business Standard
19 minutes ago
- Business Standard
Apple faces AI delay, app store scrutiny and rivals' smart glasses push
Apple is facing an unprecedented set of technical and regulatory challenges as some of its key executives are set to take the stage on Monday at the company's annual software developer conference. On the technical side, many of the long-awaited artificial-intelligence features Apple promised at the same conference a year ago have been delayed until next year, even as its rivals such as Alphabet's Google and Microsoft woo developers with a bevvy of new AI features. Those unfulfilled promises included key improvements to Siri, its digital assistant. On the regulatory front, courts in the US and Europe are poised to pull down the lucrative walls around Apple's App Store as even some of the company's former supporters question whether its fees are justified. Those challenges are coming to a head at the same time US President Donald Trump has threatened 25 per cent tariffs on Apple's best-selling iPhone. Apple's shares are down more than 40 per cent since the start of the year, a sharper decline than Google and also lagging the AI-driven gains in Microsoft shares. Apple has launched some of the AI features it promised last year, including a set of writing tools and image-generation tools, but it still relies on partners such as ChatGPT creator OpenAI for some of those capabilities. Bloomberg has reported that Apple may open up in-house AI models to developers this year. But analysts do not believe Apple yet has what technologists call a "multi-modal" model — that is, one capable of understanding imagery, audio, and language at the same time — that could power a pair of smart glasses, a category that has become a runaway hit for Meta Platforms. Google said last month it would jump back into this category, with partners. Such glasses, which are far lighter and cheaper than Apple's Vision Pro headset, could become useful because they would understand what the user is looking at and could help answer questions about it. While Apple has focused on its $3,500 Vision Pro headset, Google and Meta have seized on the smart glasses as a cheaper way to deploy their AI software prowess against Apple in its stronghold of hardware. Meta Ray-Bans all sell for less than $400. Analysts say Apple needs to answer that challenge, but that it is not likely to do so this week. "I'm not trying to replace my phone — this is a complementary thing that gives me more world context, because it's got a camera and it sees what I see, and I can talk to it in natural language," said Ben Bajarin, CEO of technology consultancy Creative Strategies. "Apple is not positioned to do that." To be sure, Apple's rivals are not decisively ahead in smart glasses. Anshel Sag, principal analyst with Moor Insights & Strategy, said Meta's Ray-Bans still lack some features and Google has not yet landed its "Gemini" model in a mass-market pair of glasses yet. "Meta has the undisputed lead, but Google is catching up fast and probably has the best-suited AI for the job," Sag said. "Vision Pro is great, but it's a showroom product that developers can use." But Bob O'Donnell, CEO of TECHnalysis Research, said it remains far from clear that smart glasses will gain wide acceptance. O'Donnell also said it is not certain that Apple is at any particular disadvantage if it partners with a company such as Google, OpenAI or even a smaller firm like Perplexity for core AI technology. So far, O'Donnell said, there is not yet strong evidence that consumers are basing major hardware-purchasing decisions on AI features. "There's an argument to be made that it's OK that (Apple) is behind because, except for the bleeding edge, most people don't care," O'Donnell said.
Time of India
an hour ago
- Time of India
Retargeting needs a creative reboot
For every customer who visits a brand's website but leaves without making a purchase, retargeting ads have long been the go-to strategy for marketers aiming to convert them. However, once the go-to for converting warm leads, retargeting is slowly losing its edge. As it reaches a plateau, marketers must reconsider where their approach may be falling short. But before we dive into the cracks in the system, let's take a moment to understand what retargeting involves. Unlike typical banner ads, retargeting ads are a form of online advertising served to people who have already visited a brand's website or are in contact with the brand. According to Criteo, only 4% of site visitors end up making a purchase. This leaves marketers with a pressing question: How do you convert the 96% who left without buying? Retargeting. However, as the saying goes, 'Retargeting works, until it doesn't.' While the concept seems foolproof on paper, real-world execution is fraught with challenges. Let's break them down one by one. Dynamic Landing Pages As an increasing number of Indians join social media to connect with their friends and family, Meta and Google have become the top advertising platforms for retargeting customers. They dominate retargeting by leveraging vast user data to serve ads based on browsing behaviour, past purchases and search history. Every time a customer clicks on a retargeting ad, they are directed to a landing page (web page designed to receive traffic from that specific ad. These platforms use static ads (fixed content pieces that remain the same regardless of context) that work well for categories like e-commerce and retail, but have limited applicability for more complex categories like insurance, where dynamic, personalised content is essential to engage users and drive conversions. Rohitesh Sahu, associate vice president - digital marketing , PolicyBazaar, pointed out this mismatch and said, 'Imagine visiting an e-commerce app to view a pair of shoes. That product page looks the same for everyone and no personal inputs are needed to see the price. In contrast to e-commerce, customer journeys in insurance are highly personalised. Quotations and policy details depend on individual data, such as age, health status, smoking habits and more.' Conventional retargeting ads offered by Meta and Google rely on audience pools, where customers are segmented based on predefined triggers like site visits or cart abandonment. These ads are usually templated and automated, directing customers to static landing pages (look the same for everyone). Serving a dynamic landing page on these platforms is not a straightforward task as insurance products often involve a longer and more complex decision-making process. Consumers typically go through several steps, reading about plans, comparing quotes and sometimes speaking with agents, before making a purchase. Because of this fragmented journey, showing a perfectly tailored landing page based on just one ad click becomes challenging, as it's hard to pinpoint exactly where the user is in the buying process. Moreover, platforms like Meta and Google have limited the use of PII (Personally Identifiable Information) due to privacy concerns. Dynamic landing pages often rely on personal customer data to tailor content. For insurance products, tailoring based on age, health conditions, or income could raise compliance flags or breach privacy norms. The challenges of serving dynamic landing pages make it significantly harder for categories like insurance to run effective retargeting ads. Diminishing Returns When a customer browses a shirt on an e-commerce site but doesn't purchase, they're often overwhelmed with static retargeting ads, nudging them to buy. These ads typically showcase the shirt, its price and discounts, but their static nature can feel repetitive and saturating. This lack of dynamism risks being ignored by customers. Dynamic ads offer a solution, but the challenge remains: are there truly 50 unique ways to advertise a single shirt? Likely not, and this is where marketers face a dilemma. Manan Bajoria, group VP - growth marketing, Ixigo, elaborated on the challenge and said, 'There's little room for creativity in retargeting ads. Even with videos or GIFs, the core message stays the same: the shirt and its price. This repetition is what makes retargeting ads feel monotonous.' When creatives remain largely unchanged, the customer experience becomes monotonous and intrusive. For instance, a user might search for a product, see related ads, return later to make a booking and then search again, only to be shown the same ads all over again. This repetitive cycle continues because the creative content doesn't evolve meaningfully over time, making the retargeting feel stale and overbearing. What remains to be seen is how technologies like agentic AI can enable brands to present a shirt in 50 unique ways during retargeting. Frequency Caps Have you ever felt annoyed scrolling through social media, seeing the same ad from a brand over and over again? Repeated exposure can lead to ad fatigue or worse, push your brand into the customer's blind spot, where they become indifferent to your messaging. To prevent overexposure, marketers use frequency caps to limit ad displays. These caps ensure brands don't overwhelm customers. Sounds simple to implement? It's not. As per Vishal Agrahari, VP - digital paid media, Bcwebwise brands typically allocate 5% to 10% of their campaign budgets to retargeting, yet often fail to achieve the desired results. A key reason, he explains, is that marketers tend to overexpose customers to retargeting ads. They repeatedly bombard users with the same creatives, failing to implement proper frequency caps—believing that more impressions equate to better recall, without realising this can lead to negative brand perception. Sharing an example of a failed retargeting campaign by a D2C brand, he said, 'A D2C apparel brand in the last quarter of 2024 had executed an aggressive retargeting campaign on Meta and Google. The campaign budget was INR 15–20 lakh per quarter allocated for retargeting, as the audience pool for remarketing was around 4 lakh users. Since they were offering discounts on products, they wanted to reach out to everyone who visited their website. But the retargeting campaign failed miserably. ROAS dropped from 3.6 to 1.4. Conversion rate went below 1%. Where they went wrong was, the audience saw the same creatives over 10 times without any frequency caps.' But why is implementing frequency caps so difficult? Here are two reasons: 'Different teams manage different channels: someone runs paid ads, another handles CRM (Customer Relationship Management) and WhatsApp, and a different team manages the call centre. It is challenging to tie one customer across these platforms and track all communications from each channel while implementing the frequency caps,' Sahu (PolicyBazaar) articulated. Highlighting the fragmented nature of digital marketing, Kedar Ravangave, EVP - marketing, Kotak Mahindra Bank, said, 'Digital marketing operates in a fragmented ecosystem, where consumers encounter ads across independent platforms like Instagram, YouTube, or news websites. This disintegration complicates tracking a user's cumulative ad exposure, as some of these platforms operate in isolation, making it difficult to manage frequency effectively. A user might encounter the same ad across Instagram, YouTube and Facebook, with no unified system tracking these repeated exposures.' Incrementality When evaluating retargeting, it is important to take into account the incremental cost—the additional expense required to achieve results that wouldn't have occurred otherwise. While retargeting may appear to be a fraction of the cost of new user acquisition, it can sometimes be up to 'ten times' more expensive when factoring in these hidden incremental costs. To demonstrate how retargeting often ends up being more expensive than new user acquisition, Bajoria conducted an experiment at Ixigo five years ago. Explaining the experiment, he said, 'When I joined the company, we were investing heavily in retargeting campaigns, spending significant budgets to re-engage users who dropped off in the funnel. To evaluate the impact of retargeting, we ran an incrementality test, dividing our audience into a target group and a control group. The test withheld ads from 20% of users while showing them to the remaining 80%, running the campaign for two weeks to compare conversion rates between the two groups. The control group, which didn't see the ads, had a 5% conversion rate, while the group exposed to ads converted at 5.5%. This meant that only 0.5% of conversions were incremental, with the remaining 5% occurring naturally, regardless of the ads. Despite Meta attributing the full 5.5% to our campaign, making the cost per booking appear favourable, the actual cost per booking was 10 times higher, revealing the inefficiency of our retargeting efforts.' To put this into perspective, imagine you run a travel website and show retargeting ads to 100 people who visited but didn't complete a booking. You spend INR 300 per booking, which seems like a bargain compared to the INR 1,000 it typically costs to acquire a new customer. However, if only 10 of those 100 bookings actually happened because of the ads and the remaining 90 either would have booked later as they were still planning their travel or didn't book at all—your real cost per incremental booking is actually INR 3,000. That's three times the cost of acquiring a new customer, not one-third as it initially appeared. Armed with these insights, Ixigo decided to halt all retargeting campaigns on Meta and Google. Now the question arises: if the actual cost of retargeting is so high, why do marketers continue to ignore the incremental cost of retargeting? 'Many marketers either aren't familiar with incrementality or know the term but don't fully understand how to measure it. They may not go the extra mile to decode its real value or simply lack the tools to do so. Often, performance metrics focus on user acquisition at low costs, making retargeting appear efficient. Without the intent or capability to dig deeper, most marketers do not want to take the bold call of just shutting down a channel,' Bajoria resolved. By allocating the money spent on retargeting to new user acquisition and targeting customers via email and WhatsApp, Ixigo's retargeting budgets have decreased by 90% compared to their previous levels, thanks to the shift to CRM channels such as email, SMS and push notifications. Vague Intent While retargeting is already a complex challenge for D2C brands, requiring a deep understanding of customer behaviour, it becomes even more challenging in the B2B space, primarily due to the lack of clear buyer intent signals. Describing this challenge, a source told ETBrandEquity, 'A major hurdle in B2B marketing is the absence of clear intent signals. Marketers often rely on vague indicators or market whispers that suggest a potential customer might need their solution, but where do you find these signals? They're rarely available in a real-time or easily accessible format. If you're trying to sell to a B2B customer, how would you even know which product they are actively exploring? Without behavioural or contextual signals, retargeting becomes a shot in the dark.' Closing The Loop Another challenge that adds to the fatigue of customers is when these static ads pop up even after the product has already been purchased. But why do customers keep receiving these ads after purchasing? Explaining, Sahu said, 'When campaigns are created, they typically involve both a targeting list and an exclusion list. For instance, if a user visits your website, brands may choose to target them with ads for the next seven days. However, it's critical that after those seven days, the user is automatically removed from the targeting list. Marketers sometimes fail to establish clear rules for exclusion lists and overlook the importance of excluding users who have already reached a key milestone in the customer journey. Without a defined and automated exclusion process, these users continue to receive ads, leading to wasted ad spend or worse, pushing the brand into the consumer's blind spot.' To manage this, PolicyBazaar structures campaigns around the customer's buying cycle. For example, in the case of car insurance, the brand knows that most purchases occur about a week before the due date. Therefore, it aligns its campaigns accordingly and avoids targeting beyond this window. A Tech Challenge Marketing professionals highlight a key gap in the current retargeting infrastructure: 'If I need to track specific customers, analyse historical data and estimate the potential dollar value from retargeting them, there's no solution that consolidates all campaigns, target bases and expected outcomes for me in one place,' says one of them, who prefers to stay anonymous. He stressed the need for a smarter, goal-oriented system. 'When I input a desired conversion rate or KPI, the system should interpret that goal and recommend the exact set of actions required to achieve it. Today, this entire process is manual,' the anonymous source added. He also pointed out the limitations in operational efficiency in retail, where a team member typically reviews past data and plans actions for the following week. If that person is on leave, the entire process can fall apart. Asking for a more intelligent, automated solution, he said, 'We need a customised tool that predicts potential revenue from retargeting specific cohorts—and suggests the right campaigns to execute.' Ad Fraud Retargeting is already a capital-intensive marketing exercise—now imagine the frustration of being taken advantage of in the process. Retargeting frauds exploit advertisers' efforts to reach users who've previously visited their website. Bots are programmed to mimic human behaviour, such as browsing product pages or adding items to a shopping cart. The advertiser's retargeting mechanisms then prompt the ad server to serve more ads to these fake 'leads,' ultimately draining budgets and wasting valuable impressions. Recalling an experience of retargeting fraud, Ravangave shared: 'This was a case from my past marketing experience during a large-scale retargeting campaign we were running with a major publisher. The goal was to deliver a high volume of clicks through specific messaging. As soon as the campaign went live, the publisher started reporting a significant number of clicks. But none of this traffic was reflected on our site. Had the team not set up hourly monitoring, we would have ended up wasting the entire campaign budget in just a week because it was a short-duration sale campaign. We quickly flagged the issue and reached out to the publisher. That's when we discovered the numbers were being manipulated by bots. What was reported as a million clicks was, in reality, just around a thousand.' Ravangave emphasises that ad fraud will continue to evolve, but the most effective countermeasure is building a solid, in-house measurement framework. After reviewing the challenges, let us now explore the solutions. Sequential Storytelling Retargeting efforts plateau beyond a point due to ad fatigue, audience saturation (a customer may fall in the retargeting pool of multiple brands in the same category) and privacy limitations. To overcome this challenge, Pragya Bijalwann, head of marketing, Voltas, suggests marketers explore strategies such as sequential storytelling and creative experimentation. These approaches help sustain engagement, expand reach to new audiences and drive conversions without relying solely on personalisation. Sequential storytelling is the practice of developing modular creatives that evolve with the consumer's journey, where each ad feels like a natural continuation rather than a repetitive nudge, creating an experience that resonates with consumers. Kotak Mahindra Bank utilises its in-house photo studio to create diverse, tailored campaign messages for every stage of the customer journey. Explaining this practice, Ravangave said, 'Our product stories have evolved from broad thematic narratives to focused messaging that highlights how a product solves problems or enhances a consumer's life. From there, we integrate bottom-funnel elements like creator endorsements, targeted offers and location-based nudges. We use signal-based sequencing (using browsing behaviour, purchase history and engagement patterns) to deliver relevant messaging tailored to each stage of the customer journey. This approach increased conversion by three to six times for customers exposed to a full-funnel strategy compared to traditional retargeting methods.' Sharing an alternate strategy to prevent retargeting from reaching a plateau, Amit Chaudhary, digital marketing head, Orient Electric, said, 'We continuously refresh our audience pools and watch for buying signals across categories. For instance, a bulk lighting buyer often signals home renovation—we can then remarket fans or geysers to such users. And this would work even better if we could tell the user our brand story. The conversion likelihood in retargeting is higher when brand trust has already been built through an intense narrative exposure. We have seen that when users are exposed to a strong brand narrative, our overall performance marketing, including retargeting, performs significantly better, as it's no longer just a push, it's part of a bigger story.' A MadTech Approach If marketing teams could openly complain about one aspect of retargeting, it would be the diminishing reach of various channels. Bajoria also noted a significant decline in the reach of CRM channels. For example, push notifications now reach only about 50% of users, as more customers choose to opt out of receiving them. 'SMS has been overused to the point where people rarely read them unless it is an OTP or a bank alert,' Bajoria added. 'WhatsApp remains a viable option, but it comes at a cost—approximately 80 paise per message. Moreover, WhatsApp imposes limits on the number of marketing messages a user can receive each week. Once this threshold is met, additional messages are simply not delivered,' Bajoria added further. The saturation of traditional CRM channels has led many marketers to see Meta and Google as more appealing options for retargeting. However, the high cost of retargeting on these platforms has created a dilemma: should marketers continue investing in Meta and Google at a premium, or shift focus to the more cost-effective CRM channels for their retargeting efforts? Bajoria believes that CRM channels such as emails, push notifications and SMS remain a better bet for retargeting due to their lower cost, and the dollars saved on retargeting on Meta and Google can be put to new customer acquisition. As a result, marketers are increasingly exploring new ways to retarget customers. One emerging approach involves retargeting the followers of micro and nano-influencers after running influencer campaigns with them—an audience known for significantly higher engagement rates. 'This strategy has proven highly effective because micro and nano-influencers have a strong presence within their communities and tend to drive much higher engagement. You're far more likely to trust a mother from your neighborhood promoting homemade pickles than a celebrity,' an anonymous source revealed. Dynamic Creative Optimisation The challenge of little to no variations in retargeting creatives causes fatigue, so what can brands do? PolicyBazaar is currently in the process of leveraging agentic AI and generative AI for personalised marketing communication, especially in banner and video formats. They are iterating and testing it on a small scale. 'While we believe it will not necessarily lead to dramatically different outcomes in terms of performance uplift, it should provide incremental benefits. Such as improving creative variety, reducing manual workload and enhancing operational efficiencies,' Sahu noted. The question of whether to retarget or not lacks a straightforward answer. It depends on factors like the brand's category, the length of the consideration period, and whether static ads effectively serve your audience or risk annoying them. Before launching campaigns, marketers must prioritise KYC—Know Your Customer—to build detailed customer profiles for strategic retargeting. Nevertheless, retargeting strategies must be re-evaluated with customer fatigue in mind to ensure better ROI (Return on Investment).
Time of India
5 hours ago
- Time of India
Meta in talks for Scale AI investment that could top $10 billion
Meta Platforms Inc . is in talks to make a multibillion-dollar investment into artificial intelligence startup Scale AI , according to people familiar with the matter. The financing could exceed $10 billion in value, some of the people said, making it one of the largest private company funding events of all time. The terms of the deal are not finalised and could still change, according to the people, who asked not to be identified discussing private information. A representative for Scale did not immediately respond to requests for comment. Meta declined to comment. Scale AI, whose customers include Microsoft Corp. and OpenAI, provides data labeling services to help companies train machine-learning models and has become a key beneficiary of the generative AI boom. The startup was last valued at about $14 billion in 2024, in a funding round that included backing from Meta and Microsoft. Earlier this year, Bloomberg reported that Scale was in talks for a tender offer that would value it at $25 billion. This would be Meta's biggest ever external AI investment, and a rare move for the company. The social media giant has before now mostly depended on its in-house research, plus a more open development strategy, to make improvements in its AI technology. Meanwhile, Big Tech peers have invested heavily: Microsoft has put more than $13 billion into OpenAI while both Inc. and Alphabet Inc. have put billions into rival Anthropic. Part of those companies' investments have been through credits to use their computing power. Meta doesn't have a cloud business, and it's unclear what format Meta's investment will take. Chief Executive Officer Mark Zuckerberg has made AI Meta's top priority, and said in January that the company would spend as much as $65 billion on related projects this year. The company's push includes an effort to make Llama the industry standard worldwide. Meta's AI chatbot — already available on Facebook, Instagram and WhatsApp — is used by 1 billion people per month. Scale, co-founded in 2016 by CEO Alexandr Wang, has been growing quickly: The startup generated revenue of $870 million last year and expects sales to more than double to $2 billion in 2025, Bloomberg previously reported. Scale plays a key role in making AI data available for companies. Because AI is only as good as the data that goes into it, Scale uses scads of contract workers to tidy up and tag images, text and other data that can then be used for AI training. Scale and Meta share an interest in defense tech. Last week, Meta announced a new partnership with defense contractor Anduril Industries Inc. to develop products for the US military, including an AI-powered helmet with virtual and augmented reality features. Meta has also granted approval for US government agencies and defense contractors to use its AI models. The company is already partnering with Scale on a program called Defense Llama — a version of Meta's Llama large language model intended for military use. Scale has increasingly been working with the US government to develop AI for defense purposes. Earlier this year the startup said it won a contract with the Defense Department to work on AI agent technology. The company called the contract 'a significant milestone in military advancement.'
