Digital Marketing Strategies: CSR, SEO, SEM, and AI

Posted on Dec 17, 2024 in Other subjects

Corporate Social Responsibility (CSR) in Social Media Marketing

1. Enhanced Brand Image: CSR actions can improve public perception of the brand, increasing customer loyalty and long-term profitability.
2. Consumer Trust: CSR shows ethical commitment, which builds trust—especially important when using social media, where transparency is valued.
3. Higher Engagement Rates: Socially responsible content encourages more interaction, shares, and comments, boosting organic reach and visibility.
4. Competitive Advantage: CSR helps medium-sized companies differentiate themselves from larger competitors, appealing to value-driven consumers.
5. Attraction of New Audiences: Millennials and Gen Z are more inclined to support brands aligned with their social values, expanding the potential customer base.
6. Risk Mitigation: CSR initiatives help preempt potential social media criticism and protect against negative publicity, reducing crisis management costs.
7. Increased Sales and Profit: Brands perceived as responsible can justify premium pricing and foster customer loyalty, leading to repeat purchases and higher profitability.
8. Employee Morale and Retention: CSR efforts can enhance company culture and attract employees who are motivated by working for ethically responsible companies, indirectly benefiting productivity and profitability.

Paid Link Building vs. Affiliate Marketing

Paid link building is not typically categorized as affiliate marketing. Although both can coexist within a comprehensive digital marketing strategy and share similarities, they serve different purposes and operate under different frameworks. Paid link building is more focused on SEO and link acquisition for authority and ranking improvement, whereas affiliate marketing emphasizes generating revenue through performance-based partnerships.

The Role of Trust in Marketing

Yes, trust is essential for building strong, long-lasting relationships with customers, fostering brand loyalty, and encouraging repeat business. Strategies that emphasize transparency, consistency, and credibility help brands establish and maintain trust with their audience.

Creating Trust with Blockchain

Using blockchain technology to create trust can indeed be a digital marketing strategy. Blockchain offers unique advantages for trust-building due to its characteristics of transparency, security, and immutability. Here’s how it can be leveraged:

1. Transparency: Blockchain enables verifiable records of transactions and data, which can be used for authenticating product origins, supply chain tracking, and verifying digital advertising metrics. This helps consumers trust that the information they receive is accurate.
2. Security: The decentralized nature of blockchain ensures data integrity and reduces the risk of data tampering. Marketers can use this to assure customers that their personal data is secure and protected.
3. Proof of Authenticity: Blockchain can be used to certify the authenticity of goods, particularly in industries where counterfeiting is an issue, such as luxury goods or pharmaceuticals.
4. Ad Fraud Prevention: Blockchain can validate ad impressions and clicks, ensuring marketers get accurate data and preventing fraud in digital advertising.

Incorporating blockchain into a digital marketing strategy can help brands stand out by promoting trustworthiness and data security, which are increasingly important to consumers.

Internet of Things: further bolsters this trust by creating a seamless automated, and highly secure ecosystem for real-time data tracking and validation.

Disadvantages of SEO

1. Time-Consuming: Achieving high organic rankings takes time and sustained effort, often months before significant results are seen.
2. Algorithm Changes: Search engines frequently update their algorithms, which can impact rankings and require constant adaptation.
3. Competitive Market: High competition for popular keywords can make it difficult to rank, especially for smaller or newer sites.
4. Ongoing Maintenance: SEO is not a one-time effort; it requires continuous optimization, content updates, and technical audits.
5. Uncertain Results: Despite best practices, there is no guaranteed outcome due to changing algorithms and competitor actions.

Disadvantages of SEM

1. Cost: Running paid campaigns can be expensive, especially in highly competitive industries with high CPC (Cost Per Click) rates.
2. Temporary Impact: Once you stop paying for ads, the visibility and traffic generated by SEM disappear immediately.
3. Ad Fatigue: Users may become desensitized to paid ads, leading to lower click-through rates over time.
4. Requires Expertise: Effective SEM involves complex campaign management, keyword bidding, and budget optimization, which may necessitate professional assistance.
5. Potential for Low ROI: If campaigns are not properly targeted or optimized, they can result in a low return on investment and wasted ad spend.

SEO is cost-effective and builds long-term credibility but requires significant time and effort, while SEM provides quick results but comes with higher costs and temporary effects. Combining both strategies can balance their advantages and mitigate their drawbacks.

Direct Marketing

Basic Characteristics

• Looking for an immediate response
• Great Database – to identify Target Audience and track response.
• Efficient Targeting – Database helps target specific individuals or (small) groups.
• Accountability – tracking response to control Content and Cost:
  • Determine the actual Costs associated with particular responses.
  • Opportunity of Predicting and Measuring responses

Channels: traditional direct marketing, new media direct marketing (SMS, messaging apps, in app push messages), social media (only if personalized)

Email Content Tips

Email Subject

• Short with action verb (max 8-10 words).
• First 3 words = most important.
• Be specific; avoid generic terms like “Newsletter.”
• Use correct punctuation; avoid caps, exclamations, and asterisks.
• Subject = promise, body must deliver.

Email Body

• Relevant, connected to the subject.
• Key info in the first paragraph.
• Use bullet points for main benefits.
• CTA buttons should engage and link to a landing page (use bright colors).
• Avoid generic terms like “Sign up”; use more engaging language.
• Personalize greetings and signatures.

Email Body & Footer Essentials

MUST include:

• A: Contact information.
• B: Easy unsubscribe (OPT-OUT).

SHOULD include:

• C: Link to data protection policies (GDPR, LOPDGDD, LSSI-CE).
• D: OPT-IN explanation for why the email was sent.
• E: Social media links.

Lead Generation

A lead is an individual or entity that has shown interest in a company’s product or service (P/S)

A lead represents an opportunity to achieve a sale or conversion.

Lead Scoring

A technique used in marketing and sales to assign a numerical value or score to potential customers (leads).

Lead Nurturing

Necessary – many times the sale does NOT occur customer’s first interaction with our website.

51% of marketers need 5 or more interactions in their lead nurturing campaigns. If you want the Customer to BUY from you, you need to get in front of them several times before they do.

Performance Marketing

Digital advertising

• PAID SEARCH: SEM
• DISPLAY advertising (web Ads) (Text Ads, Images Ads, Rich media, video Ads, banners, popup Ads) AND Programmatic Display Advertising
• SOCIAL MEDIA advertising (Twitter, Facebook, Instagram, Linkedin)
• Online VIDEO advertising (Programmatic TV Advertising)

Context-Based Advertising

Attribute-Based Advertising

Attribute-Based Advertising & Real-Time Bidding (RTB)

Involves the automated purchase of digital ad space in real-time through an auction process. It allows advertisers to target specific user attributes effectively, ensuring that the ad reaches the most relevant audience.

SSP (Supply-Side Platform) – For Publishers

Supply-Side Platform

• Companies providing Ads to websites.
• They PAY money to NYT.
• They get paid by DSP.
• They Supply relevant websites to place the Ads to concrete Target Audiences.

DSP (Demand-Side Platform) – For Advertisers

Want to PAY money for placing Ads in websites relevant for their Target Audience

Demand-Side Platform

• Companies providing Ads to SSP.
• They PAY money to SSP.
• They get paid by Singularity University.
• They Demand relevant websites to place Ads for a concrete Target Audience

Formula: Ad Position = Max Bid x Quality Score

Components

1. Max Bid (€): The maximum cost-per-click (CPC) the advertiser is willing to pay for each click.
2. Quality Score:
   • Expected Click-Through Rate (CTR): Reflects past user engagement.
   • Landing Page Experience: Evaluates the relevance and quality of the landing page.
   • Ad Relevance: Measures how closely the ad matches user queries.

This system ensures that ads shown are both valuable to users and cost-effective for advertisers.

The Perfect Quality Score

1. Select perfectly your TARGET AUDIENCE – to increase Ad RELEVANCE & USER EXPERIENCE.
2. Create a great LANDING PAGE – To increase LANDING PAGE EXPERIENCE, meeting your TARGET AUDIENCE requirements. Providing them valuable content. Based on the KEYWORDS (like on-page SEO) to increase Ad RELEVANCE
3. Create the KEYWORD LIST that will activate the Ads. – Must match the KEYWORDS of the Landing Page to increase the Ad RELEVANCE
4. Create the AD – Must include the KEYWORDS of the keyword list (activating the Ad) to increase the USER EXPERIENCE as will increase the CTR.

Must include a link to the Landing Page to increase the USER EXPERIENCE and the AD RELEVANCE.

Meta Ad Relevance Diagnostics

Metrics to give advertisers insights into how their Ads are performing and where they could make improvements.

• Quality Ranking: Compares the perceived Quality of your Ad to Ads targeting (competing) for the same audience.
• Engagement Rate Ranking: Compares the expected Engagement rate of your Ad to Ads competing for the same audience.
  • Similar to Google Ads “Ad RELEVANCE”
• Conversion Rate RankingCompares the expected Conversion Rate (CTR) of your Ad to Ads that had the same optimization goal and competed for the same audience
  • Similar to Google Ads “USER’s PAST EXPERIENCE (UX)

Personalized Targeting

One-to-One Based Targeting

Is a highly personalized approach in marketing that focuses on delivering unique, tailored messages to individual customers based on their specific preferences, behaviors, and past interactions.

Data Management Platform

• Platform for storing and analyzing data. It collects, organized and manages data from various sources

Look-Alike Audience Targeting

• Is a marketing strategy that identifies and targets new potential customers who share characteristics with a brand’s existing high-value customers
• Ads targeting more people LIKE your existing Audience.
• Allows advertisers to find potential future customer

Attribution Models

Set of rules defined to attribute the success of a conversion between various marketing events called touchpoints, set of them called user path.

Types of Attribution Models

First Generation Attribution Models

Models using simple and fixed rules, based on the position of the touchpoints in the user paths.

Based on a SINGLE touchpoint

Generate Non-Multi-Channel Reports for each Conversion

• First interaction (first click) 100% attributes conversion to first touchpoint of user path
• Last interaction (last click) 100% conversion attributed to last touchpoint in user path.
• Last indirect click (last non-direct click) conversion attributed to last click that is NOT part of direct channel.

Based on MULTIPLE touchpoints

Generate Multi-Channel Funnels reports for each Conversion

• U-shaped – Position-based – 40% of conversion attributed to first and last touchpoint. remain 20% equally distributed rest touchpoints
• Lineal – attribution is distributed evenly and equally among all touchpoints in the user path
• Time decay – Each touchpoint has a value proportional to its position in the user path, so that those touchpoints closer (in time) to the Conversion have more value.

Second Generation

• Complex models based on statistics.
• These models are also known as Data-Driven attribution models.
• They take into account the information from the user path in order to infer the impact of each of the conversion touchpoints.

MTA (Multi Touch Attribution) Model

Traditional MTA models DO NOT take into account spending on offline channels (TV, radio) or external factors (economy, COVID, specific dates)

Heuristic Models

We defined a relatively arbitrary rule and applied it.

• Based on a single touchpoint (first click, last click, last non-direct click)
• Based on multiple touchpoints(U-shaped, lineal, time decay)

Data-Driven Attribution (DDA) Models

• In the middle of the heuristic models (extreme models) there are many grays=> STATISTICS !!!
• Shapley’s Value Model
• Markov chain-based model

What Counts as a Session

• In Analytics, a session initiates when a user either opens your app in the foreground or views a page or screen and no session is currently active (e.g. their previous session has timed out).
• By default, a session ends (times out) after 30 minutes of user inactivity. There is no limit to how long a session can last.

Parameters UTM (Urchin Tracking Module)

Additional variants of URL parameters used by marketers TO TRACK the effectiveness of online marketing campaigns

Why Use Data-Driven Attribution (DDA) Models?

1. A different model is created based on the data input.

• This means that there is a specific attribution for each data set. The model varies!
• It allows you to offer personalized models for each advertiser, and even more for each campaign you activate.

2. Data-driven models, as well as the more sophisticated models of the first generation (e.g. linear model) use all the information available from the user paths.
3. First-generation model models exclusively use user paths that convert.

• If we take into account that, generally, the conversion rate is less than 1%, we would be discarding 99% of the available information.

Limitations of Data-Driven Attribution

X Data-Driven Attribution (actionable) models must be interpretable in order to translate results into decisions.

X It is unknown what data exactly these models should use as input in order to be efficient.

• Some real implementations of these models have chosen to use only the last 4 touchpoints of the user path, which could be insufficient.

Content Marketing

• Is a strategic marketing approach focused on creating and distributing VALUABLE and RELEVANT CONTENT to attract and retain a specific target audience and ultimately drive profitable action from a customer
• Aimed at satisfying information or needs of your Target Audience.
• Includes:

• Blogs
• Social Media Posts (organic)
• Microsites (small websites)
• White papers, ebooks, tutorials
• Podcasts
• Video, Videoblog, courses, webinars
• Generation of Support Material: texts, images, infographics, video…

Gen-AI Keywords: Model Types and Architectures

LLM – Large Language Models

AI models designed to handle and generate human-like text. Usually based on Transformer architecture. GPT (Generative Pre-trained Transformer) series, ChatGPT, Claude, Gemini…

Foundational Model

A general-purpose AI model trained on a broad and diverse dataset.

Specific Model

Foundational model after fine-tuning or adapted for specific tasks or domains.

Frontier Model

The latest, most advanced AI models at the cutting edge of current AI capabilities.

LLM Agents

AI systems built upon LLMs that are designed to act autonomously in various environments. They can take inputs, process information, generate responses, and interact with other systems or users to accomplish specific tasks.

Gen-AI Keywords: User Interaction

Context Window

The range of input that a model can consider when generating output, crucial for maintaining coherence and context in AI-generated text. INPUT + OUTPUT

Prompt

Prompt Engineering

Method of designing input prompts to guide the model’s responses, an essential part of interacting with and extracting useful results from generative AI.

Can You Copyright AI-Generated Content?

Human Authorship Required for Copyright

• European copyright law protects works created by human authors.
• AI systems are not legal entities and cannot hold copyright.

AI Copyright Legal Battles

Getty Images vs. Stability AI: Allegations of using millions of images without licenses. Wait-and-see approach for future AI copyright policies.

Legal Limbo for AI-Generated Works

AI-generated works currently fall into a grey area without clear protections.

• Lawmakers in Europe and globally are working to address AI copyright issues.

Implications for the Future

As AI becomes more sophisticated, intellectual property laws will need to evolve.