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July 08, 2021 8:00 AM


Top global brands, such as Spotify, Starbucks, and Cadbury, have adopted predictive personalisation approaches using powerful model-based data inputsTop global brands, such as Spotify, Starbucks, and Cadbury, have adopted predictive personalisation approaches using powerful model-based data inputs

bet-tracking-software,By Dimpy Yadav

basketball-cards-vending-machine,Advances in data, technology, and measurement promise a positive shift in outcomes for brands. Yet most brand marketers feel they are under-equipped to deploy data-triggered advertising communications.

As we imagine a post-pandemic world, we have a chance to revitalise, to use data to connect user journeys across time and across channels, wielding unified buying strategies. Brand marketers can now create more personalised and human user journeys.

Data is recognised as a prime driver of marketing success. As adoption of digital devices and participation in social networks continue to expand, so have consumers’ expectations of having relevant experiences in their interactions with brands. Consumers know exactly what they want and are drawn toward the brands that can identify and deliver to their needs. Brands must craft a robust, strategic approach to remain close to their consumers in an increasingly competitive marketplace.

The future of consumer engagement will be shaped by how effectively a brand can personalise messaging and customise products and services. Brands that do not incorporate an element of personalisation risk losing consumer engagement and loyalty. Data is crucial for personalisation at scale, delivering the perfect creative that’s targeted systematically across every touchpoint.

By focusing only on efficient media delivery and user acquisition, marketers often neglect the key to the bottom line: real ROI. By 2025, 80% of marketers who have invested in personalisation will abandon their efforts due to a lack of ROI, the difficulties of managing customer data, or both, according to a Gartner study.

The brands that win will be the ones with a media approach that embraces optimal outcomes. Campaigns that are personalised based on only consumer behaviour or audience personas are not hitting the mark, because consumers’ perceptions and purchase patterns change rapidly — a fact amply demonstrated over the past year. Brands need to rapidly evolve and respond to change by targeting consumers using highly relevant and customised messaging and offers. Consumers can no longer be identified simply as data segments but instead must be seen as individuals with frequently changing needs.

AI leads the shift

In the new age of media, brands need to leverage artificial intelligence (AI) and machine-learning technologies that index unprecedented amounts of real-time data points. This shift will provide highly targeted, customised, and hyper-personalised experiences to consumers. Brands should focus on marketing strategies driven by data, technology, analytics, and AI to gain insights and capture audiences in real time. Hyper-personalisation is pushing the industry beyond consumer segmentation and allowing brands to tailor their marketing approaches with advanced, AI-driven recommendation engines and connection of online and offline sales channels.

The journey of consumer personalisation for brands began with personal mailings or other messaging systems, which grew into behavioral segmentation. This was followed by the rise of dynamic creative ad studios’ work, optimised with omnichannel approaches.

Now brands have advanced to predictive personalisation dominated by algorithms and machine-learning models. These models profile the consumer journey and factor in cues based on previous visits, geographical data, and preferences. Then recommendation engines offer products or services curated for each consumer. Based on a consumer’s potential to engage or convert, the engines provide real-time, dynamic offers and discounts. Conversational chatbots get brands even closer to a consumer’s needs, and an omnichannel media approach connects consumers’ online and offline shopping channels.

Top global brands, such as Spotify, Starbucks, and Cadbury, have adopted predictive personalisation approaches using powerful model-based data inputs to empower recommendation engines and personalise experiences for individuals. For example, Cadbury leveraged AI for a festive campaign by creating hyper-personalised ads that promoted local retailers to consumers in geo-targeted areas.

According to a report in 2019, we will see three major shifts in personalisation by 2024. First, the report says, “physical spaces will be digitised” to provide in-store personalisation to customers as brands utilise digital assets such as apps to trigger relevant offers when a customer is near or inside a store. The second shift is that “empathy will scale,” enabling machine learning to read and react to the emotional cues of consumers. (Amazon’s new Echo device capability to detect when someone is ill by recognising when altered nasal tones indicate a stuffy nose is an example). The third shift is that “brands will use ecosystems” to enable a seamless and integrated journey based on consumers’ touch points across the various stages of their decision-making process.

Harnessing data safely

With increasing data availability, brands also need to consider privacy laws and consumer sensitivities. Tough privacy and security laws such as the proposed Personal Data Protection (PDP) Bill will push advertisers to think strategically about behavior-based targeting. Although some believe that such laws will ruin personalisation, they will in fact engender more nuanced and sensitive efforts.

Brands must seek out transparent ways to collect and index data if they intend to adopt hyper-personalised media approaches. Tactics such as notifying visitors before using tracking cookies and ad IDs on websites and apps are helping brands to more effectively deploy personalisation via up-to-date user information. Data collected by brands firsthand is extremely relevant.

Over time, brands will learn to collect and leverage customer data to generate the best possible experiences for consumers, driving indisputably better outcomes that boost the bottom line.

The author is head of client engagement, Xaxis

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