#ProgrammaticAdvertising

[newengen]

Holiday 2023 Outlook for Consumers and Marketers

Inflation has been on the decline for over a year, and in June it fell to 3% - the lowest rate recorded since March 2021. Coupled with this is a steady rise in consumer confidence, which in June hit a high not seen since early 2022. And even though these trends are a step in the right direction, economic uncertainty is still expected to play a large role in the purchasing decisions being made this holiday season. Price-conscious consumers will look to cut costs by shopping the sale section, using coupons, downsizing holiday celebrations, and simply buying fewer items. With so many brands competing for share of wallet, it won’t be enough to differentiate on price alone. Instead, brands should make a concerted effort to secure share of mind right now so that they are top of mind during the holidays and beyond.

At a high level, the best way to accomplish this is twofold. First, it’s critical to embrace an audience-first, channel-agnostic mindset so that you are reaching the right audience at the right time. Once you’ve found your audience, it’s important to meet them with strong messaging that is centered on brand value. In this article, we make the case for programmatic channels as effective marketing avenues for expanding brand reach and, ultimately, nurturing long-term brand favorability (i.e., when the holidays roll around).

Changing the Narrative on Programmatic Advertising

Let’s start with some housekeeping - when we talk about programmatic, we’re referring to a method for buying ads on specific channels, including Display, Video, Audio, and Digital Out of Home. Within each channel, there are myriad ways to target audiences based on interests, behaviors, device, location, and demographics.

“When you bring up programmatic to a performance marketer, you might see their eyes glaze over - they’re imagining annoying banner ads placed on low-quality inventory that don’t drive results,” says Erin Morningstar, Director of Strategy at New Engen. This attitude is pervasive and, according to Erin, informs the two primary reasons that brands are wary of investing in programmatic advertising: concerns about brand safety and equity, and limitations of measurement. These reservations are understandable, especially if you believe that programmatic is strictly used for generating brand awareness. But Erin explains that "programmatic is more than banner ads or dynamic product retargeting - it’s the turnkey option for accessing the wealth of ad inventory outside of walled gardens and paid search."

Teka Phan, Associate Director at New Engen, adds:

It’s important to understand that programmatic buying is performance buying. It powers actionable insights into how this media drives actions and conversions across the entire marketing funnel.

The reality of digital marketing in 2023 is that brands can’t successfully grow on the Meta-Google duopoly alone (the aforementioned walled gardens). Instead, it’s essential to meet your customers, both existing and prospective, where they are. This begs the question - where are they?

Media Consumption is Changing (Rapidly)

The channel landscape is more diverse than ever, and consumers are increasingly discovering brands through podcasts, in-app ads, and music streaming services. eMarketer predicts that, by 2024, 20% of all time spent consuming digital media will come from audio. What’s more, CTV already constitutes more than 25% of the time consumers spend with digital media, yet accounts for less than 10% of digital ad spending in the US. To put this in context, Meta receives roughly 20% of ad investment despite representing just 7.6% of all digital media consumption.

This is precisely why we, as an agency, believe that brands can win on channels like digital audio, CTV, and yes, even display. It’s true that direct-buying channels are often part of a mature media mix for many brands. But the benefit of embracing a programmatic-first approach is that it allows marketers to keep an eye on performance at scale while maintaining a direct buy approach for branding-first initiatives.

The Benefits of Investing in Programmatic

Thought leaders at New Engen have identified four primary benefits to investing in programmatic:

Control: Despite some preconceived notions, programmatic ad buying affords marketers tighter control over targeting, placements, and optimization. This level of control enables measurement testing in the form of geo holdouts, known audience split tests, and platform lift tools. Such exercises are critical to proving the value of channels outside of last-click.

Flexibility: Budgets can be seamlessly moved around across channels and publishers on a daily or even hourly basis. In contrast, brands buying directly from multiple publishers are beholden to more rigidity driven by campaign minimums and contract terms.

Value at Scale: Not only are CPMs generally cheaper when buying programmatically, but DSPs often provide access to a variety of inventory types, formats, and audiences - in turn, this variation powers the development of diverse, mature programs. The inventory is virtually endless and continuing to grow as more platforms and publishers open their inventory to exchanges.

Actionable Insights: By investing in programmatic activations, brands can quickly gather learnings about what kind of inventory and formats are driving performance. While this may not be a unique function of programmatic channels, it’s differentiated by actionability - “Many people see programmatic as an upper funnel, impression-buy only. The value is that we can measure action (conversions, traffic, etc.) and then act on it in real-time,” Teka explains.

How New Engen Clients Have Found Success With Programmatic

Programmatic buying has driven strong results for New Engen clients, with brands finding synergy between their programmatic programs and other marketing channels, including Paid Search and Social. Below are two New Engen case studies that exemplify the benefits of incorporating programmatic into your marketing mix.

Unlocking Incremental Site Traffic Through CTV

In Q4 of 2022, our client, an outdoor apparel brand, tasked us with driving incremental site traffic through new channels. We first identified CTV as their target audience's top digital destination, then we built three rich consumer segments: in-market for outdoor apparel gear, recent competitor site and store visitors, and recent outdoor equipment purchasers. Ads were served across a variety of CTV platforms like Roku, Hulu, Pluto TV, and the Discovery Channel, and optimized based on insights from real-time incrementality studies.

Under this approach, our exposed audience was 2.5X more likely to visit the brand’s site than our non-exposed audience. What’s more, we achieved a 1.9X lift in checkouts. In other words, the brand was able to reach and capitalize on a more qualified audience through its CTV initiative. To top it all off, we identified a previously under-served audience as a standout performer - a learning that is pivotal to refining the program downstream.

Proving the Revenue Impact of West Marine’s Digital Video Awareness Media

In order to validate the direct revenue impact of digital video awareness media, we designed an audience holdout test for our client, West Marine. We activated precision media buys across CTV and YouTube in Florida, a key growth market for the brand. The audience segments included prospecting, retargeting, and lapsed customers, and were compared against national performance.

By the end of the two-week period, the target audience delivered a 1.7X lift in online lapsed user transactions and a 4.6X lift in in-store transactions. Omnichannel ROAS also improved, and West Marine measured a 1.4X increase in year-over-year omnichannel revenue from new-to-file customers.

Programmatic Advertising Best Practices for Holiday 2023

Whether you're bought into programmatic after reading this or just curious to learn more, we want to leave you with our recommendation for what to do next. Here's what New Engen leaders say are the most important steps to successfully incorporate programmatic into your Holiday 2023 strategy:

First and foremost, set clear objectives

→ Identifying what you want to accomplish and learn from your programmatic initiative is the most important step, as this will inform how to design your program. Before you can drive awareness with a new segment or increase AOV within an existing one, you’ll need to understand your audience - then, you can tailor your channels, targeting, and creative parameters to their specific needs. Once you’re aligned on the plan, stick to it.

Set expectations with your team

→ Know that every channel should have its own goals and benchmarks. Don’t track your programmatic performance against your Paid Search campaigns, because these are inherently different channels and so are their outcomes. Performance will even vary across, Podcast, CTV, and Display given their different mediums.

For example, a consumer who searches for “shoes” is more likely to make an immediate purchase because they are actively searching for the product. Programmatic channels, on the other hand, expose audiences to products before they are ready to purchase. So if that same consumer sees a CTV ad for a pair of shoes before they start their search, there’s a likelihood that they will have been influenced before their final purchase decision.

Launch early

→ We anticipate that the holiday season will stretch across Q4, and consumers will start their holiday planning and shopping early - you want to be there when they’re in the consideration stage. As a rule of thumb, you should be in market at least 4 weeks prior to your peak shopping period.

Anticipate different scenarios

→ As an agency practice, we create decision playbooks with our clients going into critical peak periods that allow our teams to move quickly when optimizing campaigns.

If you’re interested in chatting more about your programmatic strategy for the holidays or beyond, reach out to us at programmaticleadership@newengen.com. For more holiday insights and digital marketing news, subscribe to our newsletter and follow us on LinkedIn.

[billboards-media]

The article highlights the evolution of outdoor advertising with the rise of digital billboards, interactive displays, and programmatic advertising, revolutionizing the way brands connect with consumers. These advancements offer greater flexibility, targeting precision, and real-time analytics, ensuring more engaging and effective campaigns.

[catchexperts]

AI in Marketing 2025: Top Trends, Tools, and Ethical Challenges

By 2025, artificial intelligence is set to redefine the marketing industry. With advancements in automation, personalization, data analysis, and decision-making, AI is transforming how brands engage with customers, optimize strategies, and create meaningful experiences. However, these opportunities come with ethical and operational challenges that marketers must address.

This blog explores the most impactful AI marketing trends for 2025, the tools shaping the future, and how businesses can prepare for what's next.

1. AI-Powered Automation: Efficiency at Scale

By 2025, AI will handle up to 85% of customer interactions through intelligent chatbots and virtual assistants. This will streamline operations, reduce response times, and free human teams for high-value strategic tasks.

Example: Photobucket uses Zendesk bots to automate FAQs, improving response time by 14% and customer satisfaction by 3%.

Takeaway: Automate repetitive tasks using AI to enhance customer service and team productivity.

2. Hyper-Personalization: A New Marketing Standard

AI will push personalization beyond basic targeting, delivering dynamic, real-time experiences based on behavior, preferences, and predictive analytics.

Example: Jasper.ai enables personalized content generation across formats, improving engagement and conversion rates.

Takeaway: Use AI-driven insights to tailor content, offers, and messaging across the entire customer journey.

3. Smarter Decision-Making with AI

AI will play a central role in strategic planning and decision-making by 2025. Predictive analytics, real-time dashboards, and data modeling will guide marketing teams in making faster, smarter decisions.

Example: ClickUp AI enables teams to visualize and act on complex data, improving operational efficiency and accuracy.

Takeaway: Integrate AI into your analytics stack to enhance forecasting, reporting, and real-time marketing decisions.

4. Ethical AI and Responsible Governance

As AI adoption grows, so do concerns about privacy, algorithmic bias, and data ethics. Companies must establish governance frameworks to ensure transparency, compliance, and consumer trust.

Key Stats: In 2022, 127 countries passed AI-related laws, reflecting the global push for regulation.

Takeaway: Develop clear AI usage policies, invest in bias detection, and prioritize ethical design in all AI-driven marketing activities.

5. The Future of Work: Workforce Transformation

AI will disrupt traditional marketing roles but also create new opportunities in strategic, creative, and AI-enablement areas.

Insight: McKinsey predicts 30% of hours worked today could be automated by 2030, while 97 million new jobs could emerge.

Takeaway: Focus on reskilling your team with AI literacy, data interpretation, and creative strategy skills.

6. Emerging AI Technologies Shaping Marketing

a. Predictive Customer Insights

Deep learning will allow marketers to predict customer needs, behaviors, and buying intent with greater accuracy, enabling proactive engagement.

b. Generative AI for Content Creation

AI tools like GPT-4 will create on-brand, audience-specific content (text, images, video), cutting production time and cost.

c. AI-Driven Programmatic Advertising

AI will enable real-time audience targeting and creative optimization, maximizing ROI through smarter ad placements.

d. Sentiment Analysis & Emotional Intelligence

AI models will detect emotional tone in feedback and social media, helping brands fine-tune messaging and CX strategies.

e. AI + AR: Immersive Brand Experiences

Combining AI with augmented reality will create dynamic, personalized brand experiences, especially in e-commerce and retail.

7. Ethical Considerations in AI Marketing

Data Privacy: Companies must ensure GDPR compliance and transparency in data usage.

Bias in Algorithms: Regular audits are needed to prevent discriminatory practices.

Explainability: Brands should communicate how AI decisions affect users.

Job Displacement: Ethical adoption includes reskilling and supporting displaced workers.

Conclusion: Preparing for the AI-Driven Future

The future of AI in marketing is filled with promise and responsibility. Marketers who embrace automation, personalization, and ethical governance will gain a competitive edge. Now is the time to invest in AI tools, upskill your team, and align your strategies with this fast-evolving landscape.

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How AI is Revolutionizing Digital Marketing

As we enter 2025, the world of digital marketing is experiencing a seismic shift, and that's being led by progress in Artificial Intelligence (AI). This isn't a fad technology; it's rewriting the way marketers approach consumer engagement, campaign optimization, and data analysis. Let's get up close with how AI is transforming digital marketing and its implications for brands in the future. 1. Automation Moves to Center Stage One of the most notable effects of AI on digital marketing is automation. By 2025, it's estimated that AI will manage as much as 85% of customer interactions via chatbots and virtual assistants. This transformation enables companies to offer faster responses to customer queries and simplify operations. Improved Customer Service: Companies such as Photobucket are already leveraging AI chatbots to handle FAQs, leading to faster response times and customer satisfaction rates. Operational Efficiency: AI software can perform mundane tasks like data entry and report generation, allowing marketers to concentrate on strategic activities. 2. Generative AI Revolutionizes Content Creation Generative AI will revolutionize the way content is created in marketing. Software based on sophisticated neural networks can generate compelling content in a range of formats—text, images, or video—specific to desired audiences. Cost and Time Efficiency: Brands can save a lot of time and resources invested in content creation with generative AI. The technology is aware of brand voice and audience tastes, so the content is always engaging for target markets. Diverse Applications: Blog posts, social media graphics, and many other creative tasks can be performed by generative AI, making it an asset for marketing teams. 3. Smarter Advertising with Programmatic Solutions AI is improving programmatic advertising with real-time bidding and better audience targeting. It enables advertisers to dynamically optimize ad placements based on large data sets. Improved ROI: Through the study of user behavior and engagement data, AI makes it possible for brands to better manage their advertising budget so that they can get the most out of their investment. Real-Time Optimizations: AI platforms are able to make real-time optimizations for ad campaigns from performance data, enabling dynamic marketing strategies that can react to shifts in the marketplace. 4. Profound Insights Through Sentiment Analysis Being able to interpret customer sentiment is essential to truly effective marketing strategy. AI-based sentiment analysis solutions are developing incredibly fast, helping brands better understand human emotions through multiple channels. Proactive Engagement: Using sentiment analysis, companies can proactively respond to customer feedback, adapting their message to enhance satisfaction and loyalty. Nuanced Understanding: Vendors such as Clarabridge are spearheading the effort to create solutions offering more in-depth insights into consumer feelings and tendencies, enabling brands to create more targeted communications. Conclusion

AI is not only transforming digital marketing; it's redefining the very nature of how brands engage with their audiences. From customer automation to personalized content at scale, the advantages of merging AI into marketing strategies are tremendous. As we progress deeper into 2025, adapting to these technologies will be important for brands that seek to remain competitive in this ever-changing environment. The future of digital marketing is now—driven by AI—and it holds the key to a more streamlined, personalized, and immersive experience for consumers globally.

For More Visit : https://kprbrandingbharat.com/

[mfilterit]

AI in Programmatic Advertising Fraud Detection to Deliver Performance and Sustainability

The rise of programmatic advertising has shifted the focus towards accuracy and automation. It surged from $9.75 billion in 2023 to $12.46 billion in 2024, an annual growth rate of 27.8% and is expected to continue expanding, reaching $28.12 billion by 2028 at a compound annual growth rate (CAGR) of 22.6%. However, with AI coming into the picture, performance programmatic platforms are prone to ad fraud even more. The need for optimization of programmatic media buying with comprehensive ad fraud solution across the advertising funnel is the necessity to yield results.

Why Programmatic Ad fraud prevention?

Protect your brand with programmatic ad fraud prevention. Ensuring the invalid traffic is blocked from malicious sources not only safeguards advertising budget but also protect brand reputation.

Here’s how mFilterIt guides with trust and transparency in programmatic advertising:

Impression fraud

Impression Fraud analysis is better at the post-bid stage than pre-bid, measuring performance beyond viewability metrics. In pre-bid analysis, i.e. before the ad is served, fraud can be identified based on only two parameters, IP and User Agents. Also, the time for analysis is limited to 10 milliseconds. This results in a meager 2% fraud identification.

This is where a post-bid analysis trumps a pre-bid impression validation. Now that we have several more parameters fraud detection is done on deterministic and heuristic measures as well. This results in the detection of higher invalid impressions of 15–20%. This results in improved ROI on Ad spending. Post-bid impression analysis is a more beneficial method for detecting ad fraud.

Made for Ad sites

Advertisers spend an average of 15% of their programmatic budget on MFA sites, but some may spend as much as 42%. While 35% of programmatic spending is wasted on low-value environments like MFA sites, according to a recent study by ANA (Association of National Advertisers). By focusing on robust ad fraud detection advertisers can combat the various forms of fraud that undermine their campaigns across digital advertising platforms. Prioritizing impression validation is essential for maximizing return on investment and maintaining trust in the advertising ecosystem.

MFA Sites not only drain budgets but also pose a challenge to a brand’s safety. Limited reach and exposure, no real user engagement misleading clicks, click fraud, artificially inflated metrics, poor conversion rates, low-quality/intent traffic and brand un-safe content tarnished brand image and lead to budget drainage.

Programmatic Advertising Fraud in USA, UAE, India, Dubai.

Click here to read more about the: AI in Programmatic Advertising Fraud Detection to Deliver Performance and Sustainability

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Best Online Advertising Strategies | Google Ads, Facebook Ads | Online Advertising

In today's digital landscape, businesses need strong online advertising strategies to maximize reach, increase sales, and boost brand awareness. With the right mix of Google Ads, social media advertising, and programmatic advertising, businesses can drive targeted traffic and generate high returns on investment (ROI).

In this guide, we’ll explore the top advertising platforms, strategies, and expert tips to advertise your business effectively in 2025.

1. Google Ads: The Most Powerful Online Advertising Tool

Why Choose Google Ads?

Google Ads is the most effective way to promote your business on the world’s largest search engine. With multiple ad formats, including Google Search Ads, Google Shopping Ads, and Google Pay Per Click (PPC) campaigns, businesses can reach highly targeted audiences.

Google Ads Pricing & Cost

The average Google Ads cost varies based on competition and industry.

The cost per click (CPC) can range from $1 to $10+ for competitive keywords.

Hiring a Google Ads specialist or Google Ads agency can help you optimize your campaign for better ROI.

Google PPC vs. Google Search Ads

Google PPC (Pay Per Click) charges you for every click on your ad.

Google Search Ads appear when users search for specific keywords.

Google Shopping Ads are ideal for eCommerce businesses looking to promote products.

Need help? A professional Google Ads expert can create and manage your campaigns for maximum effectiveness.

2. Social Media Advertising: Facebook, Snapchat, Twitter & More

Social media platforms offer incredible opportunities to advertise your business. Here’s how you can leverage them:

Facebook Advertising & Meta Ads

Facebook Ads are one of the most powerful digital marketing tools.

With Meta Ads, businesses can run ads across Facebook, Instagram, and Messenger.

Facebook Advertising Costs depend on audience size, ad placements, and bidding strategies.

Snapchat Ads Manager

Snapchat Ads are great for targeting younger demographics.

Businesses can use Snapchat Ads Manager to create engaging vertical video ads.

Twitter Ads

Twitter Ads allow businesses to promote tweets and reach a wider audience.

It’s an excellent platform for brand awareness and customer engagement.

Spotify Ads

Spotify Ads let businesses run audio and video ads on the popular streaming platform.

These ads can be highly engaging and are great for brand storytelling.

Business Advertising with Social Media Agencies

If managing social media ads seems overwhelming, hiring a social media agency can streamline your advertising strategy and ensure high ROI.

3. Programmatic Advertising: The Future of Digital Marketing

What is Programmatic Advertising?

Programmatic advertising automates the buying and placement of online ads in real-time, ensuring businesses get the best ad placements at competitive prices.

Why Use Programmatic Advertising?

Maximizes ad efficiency and reduces costs.

Uses AI-driven bidding to reach the right audience.

Works across Google Ads, display networks, and social media platforms.

4. Additional Advertising Strategies for Business Growth

Billboard Advertising

Traditional billboard advertising remains effective, especially for local businesses.

Combining digital and physical advertising can create a powerful brand presence.

Promote Your Business for Free

Use free advertising methods like SEO, content marketing, and organic social media.

Engage with customers using Hootsuite and Sprout Social for cost-effective marketing.

Explore Sprout Social pricing and Hootsuite pricing for affordable social media management.

Advertise My Business: Best Practices

Run a Google Ads campaign for instant traffic.

Use social media advertising for brand engagement.

Consider billboard advertising for local brand awareness.

Partner with a professional advertising agency to maximize impact.

Final Thoughts

The world of online advertising is vast, but with the right strategies, businesses can thrive. Whether you’re leveraging Google Ads, social media marketing, or programmatic advertising, having an expert-driven approach ensures long-term success.

Looking for professional digital marketing services? At Reflextick Creative Agency, we specialize in Google Ads, social media marketing, and programmatic advertising to help businesses grow.

📧 Contact Us: info@reflextick.com

🌐 Visit Our Website: https://reflextick.com

[digitalzaa]

How AI is Transforming Digital Marketing: The Future of Smart Advertising

Artificial Intelligence (AI) has emerged as a game-changer across various industries, and digital marketing is no exception. In today’s fast-paced digital world, marketers are leveraging AI to automate processes, personalize customer experiences, and optimize advertising strategies. With AI-powered tools, businesses can gain deeper insights into customer behavior, streamline content creation, and drive higher engagement.

AI-driven marketing tools have transformed how brands interact with their audiences, making campaigns more efficient, cost-effective, and impactful. From chatbots and predictive analytics to programmatic advertising and hyper-personalization, AI is reshaping the marketing landscape. In this blog, we will explore the profound impact of AI on digital marketing and how businesses can embrace this technology for a smarter advertising future.

The Role of AI in Digital Marketing

AI enhances digital marketing by leveraging machine learning, natural language processing (NLP), predictive analytics, and automation. By analyzing vast amounts of data, AI provides actionable insights that help marketers create highly targeted campaigns, improve customer interactions, and optimize ad performance.

Some key areas where AI is revolutionizing digital marketing include:

Customer insights and analytics

Personalized marketing campaigns

Automated content creation

Chatbots and AI-driven customer service

Predictive analytics and trend forecasting

Programmatic advertising and media buying

Let’s dive deeper into how AI is transforming each of these aspects.

AI-Powered Customer Insights and Analytics

Traditional market research methods are being replaced by AI-driven analytics that provide real-time insights into customer behavior. AI can process massive datasets to uncover patterns, trends, and preferences, helping marketers understand their target audience better.

How AI improves customer insights:

Sentiment Analysis: AI tools analyze customer feedback, reviews, and social media conversations to gauge brand sentiment and adjust marketing strategies accordingly.

Predictive Analytics: AI predicts customer behavior based on past interactions, allowing businesses to anticipate needs and tailor marketing strategies.

Behavioral Segmentation: AI segments audiences based on real-time data, making marketing campaigns more precise and effective.

Personalization at Scale

AI enables hyper-personalization by analyzing customer data and delivering tailored content, recommendations, and experiences. Unlike traditional personalization, which is based on demographics and past behavior, AI-driven personalization continuously adapts to user preferences in real time.

Examples of AI-powered personalization:

Email Marketing: AI optimizes email subject lines, content, and send times for each recipient, increasing open and conversion rates.

Dynamic Website Content: AI modifies website elements based on user behavior, ensuring a unique experience for every visitor.

Product Recommendations: AI-driven recommendation engines (e.g., Amazon, Netflix) suggest products based on user history and preferences.

AI in Content Creation and Curation

AI is transforming content marketing by generating, curating, and optimizing content at scale. Marketers can now automate content production while maintaining quality and relevance.

AI-driven content tools include:

Natural Language Generation (NLG): AI tools like ChatGPT and Jasper AI generate blog posts, product descriptions, and social media captions.

Content Curation: AI helps marketers find and suggest relevant content for newsletters and social media.

SEO Optimization: AI-powered tools like Clearscope and SurferSEO analyze search trends to improve content ranking on Google.

Chatbots and AI-Powered Customer Service

AI-driven chatbots are revolutionizing customer interactions by providing instant responses, resolving queries, and enhancing user experience. These virtual assistants reduce response times and ensure 24/7 customer support.

Benefits of AI chatbots:

Instant Customer Support: Chatbots handle common queries, reducing the workload on human agents.

Conversational AI: Advanced chatbots use NLP to understand and respond naturally to users.

Lead Generation: Chatbots engage website visitors, collect data, and qualify leads for sales teams.

Predictive Analytics for Smarter Decision-Making

Predictive analytics, powered by AI, enables marketers to make data-driven decisions and anticipate future trends. By analyzing historical data, AI identifies patterns that help businesses strategize effectively.

Applications of predictive analytics in marketing:

Customer Lifetime Value (CLV) Prediction: AI estimates a customer’s future spending, helping brands prioritize high-value customers.

Churn Prediction: AI identifies customers at risk of leaving, allowing businesses to take proactive retention measures.

Sales Forecasting: AI predicts sales trends based on historical performance and market conditions.

Programmatic Advertising and Smart Media Buying

AI is transforming digital advertising by automating media buying and optimizing ad placements in real time. Programmatic advertising uses AI to analyze user data and bid on ad spaces that are most likely to convert.

How AI enhances advertising:

Real-Time Bidding (RTB): AI automates bidding for ad impressions, ensuring ads reach the right audience at the best price.

Ad Performance Optimization: AI adjusts ad creatives, targeting, and budgets in real time to maximize ROI.

Fraud Detection: AI identifies and prevents ad fraud, ensuring marketing budgets are spent effectively.

The Future of AI in Digital Marketing

As AI technology continues to evolve, its role in digital marketing will expand further. Some key trends shaping the future of AI-driven marketing include:

Voice Search and AI Assistants: With the rise of voice assistants like Siri, Alexa, and Google Assistant, optimizing for voice search will become essential. AI will refine voice search algorithms, making content more conversational and accessible.

Visual and AI-Powered Search: AI-powered visual search (e.g., Google Lens, Pinterest Lens) allows users to search for products using images instead of keywords. Brands will need to optimize their visual content for search engines.

AI-Generated Video Content: AI is making video creation more accessible with automated video editing, scriptwriting, and personalized video recommendations. Expect AI-driven video ads and interactive storytelling to dominate digital marketing.

Hyper-Automation in Marketing Workflows: AI will continue automating repetitive marketing tasks, allowing marketers to focus on strategy and creativity. Expect seamless integrations between AI-driven analytics, automation platforms, and CRM systems.

Ethical AI and Data Privacy: As AI becomes more powerful, ethical concerns around data privacy and AI bias will grow. Marketers must prioritize transparency, user consent, and responsible AI usage to maintain trust.

Conclusion

AI is revolutionizing digital marketing by making campaigns smarter, more efficient, and highly personalized. From customer insights and content creation to predictive analytics and programmatic advertising, AI is shaping the future of marketing. Brands that embrace AI-driven strategies will gain a competitive edge, enhance customer experiences, and achieve better ROI.

As we move forward, the key to successful AI-driven marketing will be balancing automation with human creativity, ensuring ethical AI use, and staying ahead of evolving technology trends. The future of digital marketing belongs to those who adapt, innovate, and harness the power of AI to drive meaningful engagement and business growth.

Click here to learn more about how Digital Marketing is revolutionalizing with the help of AI.

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What Is Programmatic Advertising In Simple Words https://froggyads.com/blog/what-is-programmatic-advertising-in-simple-words-4/?utm_source=dlvr.it&utm_medium=tumblr

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Edge Computing: Extending the Power of the Cloud

When I embarked on my journey into the world of cloud technologies, I had little idea how transformative it would be. The sheer breadth of cloud concepts and services initially overwhelmed me. I found it challenging to connect theoretical knowledge with practical applications, often feeling lost amidst the jargon and complexities. However, these problems transformed into learning and understanding by following a well-defined course and experimenting with projects gradually. My foundational knowledge came from an in-depth cloud computing online course with the ACTE Institute. This established a comprehensive view of the foundational aspects of clouds, which, later in life, served as the backbone for my profession as a solution architect. Initially, it was difficult to comprehend the scope of services and technologies, but structured learning with practical examples bridged the gap.

What is Edge Computing?

Edge computing is a technology paradigm that brings computation and data storage closer to the sources of data, such as IoT edge devices, to reduce latency and improve processing efficiency. This shift also has an impact on industries, such as reducing energy consumption and operational costs. An edge device consumes bandwidth by processing information locally, not requiring constant energy to transmit the data to a centralized server. With the reduction in reliance on cloud infrastructure, such big clouds, cost-cutting happens on data transfer as well as storing in a central location, so edge computing comes out as both cost-effective and eco-friendly. This reduces reliance on centralized cloud servers, allowing the edge servers and networks to process critical tasks on-site. Edge computing has significantly improved responses, which makes this shift vital for applications such as real-time processing in autonomous vehicles, healthcare monitoring, and industrial automation.

Edge computing also cuts down bandwidth utilization and operational cost. For example, rather than sending terabytes of raw data to the cloud for processing, edge devices filter and process the data locally, transmitting only what is relevant. This improves efficiency and enhances privacy by keeping sensitive data closer to its source.

Role of Edge Servers and Edge Networks

One of the projects that we implemented recently involved using edge servers for real-time analytics for a smart city initiative. We processed IoT data from sensors in place and saved huge amounts of time on decision-making, as was demonstrated in an example involving the analysis of traffic sensor data for congestion level updates. This improved the efficiency of traffic management systems, reduced fuel consumption from idling vehicles, and enhanced overall urban mobility. Localizing data processing further also helped reduce dependency on central cloud infrastructure for computation by saving cost and improving reliability in case of network disruptions. These scattered servers acted as intermediaries between IoT devices and the central cloud, exposed to strategic locations with the required physical infrastructure for networking. Edge networks further ensured seamless communication, thus reducing latency issues that would have otherwise hampered critical operations, such as traffic management and emergency responses.

One striking example was using edge servers for monitoring traffic congestion. By analyzing data from IoT sensors on the roads, the system provided instant updates and recommendations to drivers. This reduced delays and enhanced overall traffic flow.

Multi-Access and Mobile Edge Computing

I have also looked at multi-access edge computing and mobile edge computing as part of my work. MEC is an extension of cloud capabilities to the edge of the network, presenting the solutions required for low latency in applications such as autonomous vehicles or AR/VR experiences. For example, real-time map rendering can be available for the navigation of autonomous cars in high-traffic areas.

Similarly, mobile edge computing enables mobile devices to process data locally, which can be used for smoother gaming, video streaming, and IoT applications. A recent use case I worked on was leveraging MEC for a sports analytics platform. The platform delivered instant replays and analytics to fans in real time by processing video feeds from stadium cameras locally, creating an engaging experience.

Examples of Edge Computing in Action

During my stay at ACTE, I learned the basics that later helped me design practical edge computing examples in industries like healthcare, retail, and manufacturing. For example:

Healthcare: IoT edge devices monitor patients in real-time, providing critical data to edge servers for immediate analysis. In one hospital project, we used edge technology to track vital signs and alert medical staff during emergencies, significantly improving response times.

Retail: Edge computing technology powers personalized shopping experiences by analyzing customer behavior directly at the store. For example, an edge-based recommendation system suggested products to customers based on in-store browsing patterns, boosting sales.

Manufacturing: Edge computing devices streamline production lines by analyzing machine data on-site, predicting maintenance needs, and reducing downtime. In one factory, deploying edge servers helped identify equipment malfunctions before they escalated, saving significant costs.

Edge Cloud Computing and Platforms

Cloud providers have incorporated edge computing into their services, which gives rise to edge cloud computing. In contrast to the traditional model of cloud, which relies on centralized data centers for processing and storing data, edge cloud computing disperses such capabilities closer to the sources of data. For instance, while a legacy cloud model is likely to have latency issues with the distance between users and servers, edge cloud computing is much faster in responding because data processing is done locally. In addition, edge cloud computing reduces the amount of constant data transfer to a central server, thus cutting bandwidth costs and increasing system reliability in areas where the network is unreliable. Providers like AWS Edge Computing and Akamai Edge Compute offer robust platforms that bridge cloud and edge capabilities. AWS’s services like Greengrass enable developers to run applications locally on IoT devices, allowing for offline functionality and real-time decision-making. Similarly, Akamai’s platform accelerates content delivery and application performance, making it invaluable for industries like e-commerce and media.

During a project with a media streaming company, we used Akamai Edge Compute to optimize video delivery. This means that content will be cached nearer to users in order to lower buffering times and increase viewer satisfaction. In fact, it will show how the edge cloud is enhancing customer experience in every area.

Challenges and Future Trends

Even though edge computing has great potential, it isn't without challenges. In my projects, one challenge always kept on surfacing: making sure that distributed edge locations maintained data security. Each edge server and device offered a potential weakness, necessitating sophisticated encryption and real-time monitoring solutions. A second challenge was the high deployment and maintenance costs of edge infrastructure, which meant careful budgeting and optimization strategies. For instance, in a smart city project, we addressed the above challenges by implementing a mix of lightweight security protocols and periodic audits that balanced performance with cost-effectiveness. These experiences taught me that overcoming edge computing challenges often requires a tailored approach, aligning technology with specific project needs. Security concerns, infrastructure costs, and the complexity of managing distributed networks are significant hurdles. For example, securing data across multiple edge locations requires advanced encryption and monitoring solutions, which can be resource-intensive.

However, progress in edge computing technology is tackling the above-mentioned issues one after another. Trends include introducing AI at the edge, thus making devices capable of learning in real time and adaptation. Besides this, there will be improvement in 5G networks which is expected to strengthen edge computing as well through providing fast, stable connectivity of devices and applications.

Why Edge Computing Matters

In retrospect, I think it is unbelievable how edge computing devices and technologies have changed the way we look at data processing. They extended the power of the cloud to the very edge, which makes it possible for innovative solutions in various sectors, from better health outcomes to transforming retail experiences, and many others.

So if you are also interested in taking up a career in this rapidly changing field, I would say that professional learning is the first step. This is because such a specialized course in cloud computing course in Bangalore from ACTE Institute helped me shape my career into a solution architect. The on-the-job learning and industry insight I received continue to drive me forward in both passion and results.

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