Every day, thousands of brands appear on our screens. Some stay for a second ⏱️. Others stick in our minds 🤔. Very few become part of the conversation 💬.

The difference is not just how much they invest, but how they collaborate with creators within an ecosystem that is cultural, mobile, emotional, and fragmented.

Influencer marketing, when integrated with vision, can be a strategic lever at all phases of the funnel: from generating awareness in the top-funnel with content that travels naturally, to activating consideration in the mid-funnel through credible profiles ✨, or driving performance through paid media formats and well-defined attribution models 📈.

For it to work, it’s not enough to be everywhere. It’s about knowing how to collaborate with the right profiles, respecting their codes, their community, and their value at each stage of the consumer journey.

Each platform presents a distinct set of opportunities. We don’t intend to cover everything, but rather to offer a strategic vision of how to activate with purpose and direction 🧭.

TikTok: Shared Culture and Amplified Visibility 🎶

TikTok moves fast and operates primarily at the top-funnel, generating discovery and interest through cultural participation.

But for content to connect, it must feel authentic ✅. Here, working with creators implies co-creating ideas that adapt to their language and community, rather than simply transferring a prefabricated message 🗣️.

Furthermore, the use of paid media on TikTok is key to scaling content that works. Promoting organic creator pieces allows for maintaining the influencer’s voice, while amplifying its impact with advanced segmentation and performance objectives.

Brands that understand this don’t just create viral hits. They turn visibility into conversation and brand recall 🧠.

Instagram: Building Affinity with Measurable Impact 📸

Instagram remains a central platform for developing brand consideration and fostering a constant connection with the audience. Reels, Stories, and carousel collaborations allow for a continuous, visual, and emotional narrative.

Organic content is only part of the game. Today, many brands are finding in Creator Ads an effective way to amplify collaborations with creators: content created by influencers, promoted from their profile but with media control from the advertiser. This approach combines the best of two worlds: the credibility of the creator and the targeting and optimization capabilities of paid media 🎯.

On Instagram, influencer marketing can generate both branding and performance, when planned as part of a complete system 🌐.

YouTube: Deep Influence that Informs and Converts💡

YouTube is the ideal platform for working the mid-funnel and the lower-funnel, thanks to its capacity to generate trust and deepen the message 🧐.

Here, creators have space to explain, show, compare, and validate. And that generates a type of connection that goes beyond superficial recommendations.

Additionally, YouTube offers paid media formats that allow for activating creator content as part of performance campaigns 📈.

From personalized video sequences to retargeting based on visualisations, the collaboration doesn’t end when it’s published: it’s amplified when integrated with strategy.

Well-planned, content with creators on YouTube can be both an inspiration tool and a decision-making tool, depending on the format and the moment in the funnel.

Twitch: Creating Moments that Build Loyalty 🎮

Twitch offers a different dimension of audience connection: based on shared time and an active community.

It is a loyalty channel, where brands can connect with highly engaged audiences, in participatory and authentic environments.

Here, the creator is not just a broadcaster: they are an host 🎙️. Brands that understand this collaborate from within, designing activations where the presence feels organic and meaningful.

And although Twitch is essentially organic, its effect can extend by using clips and summaries in cross-channel paid media campaigns, or amplifying key moments in networks like YouTube Shorts or Instagram Reels.

What’s important is not just the live stream. It’s how it converts into useful content beyond the broadcast💡.

X (formerly Twitter): Positioning and Amplifying Narrative 🗣️

X continues to be a relevant space for brands that want to participate in the public discourse and reinforce their positioning.

Here, the value of creators lies in their ability to influence key topics, with a recognized voice and an attentive audience 👀.

Organic content can have great contextual impact, but it can also be activated as part of paid strategies, amplifying threads, collaborations, or messages aligned with cultural moments or specific junctures.

In many cases, influencer marketing on X is boosted when it aligns with causes, values, or relevant positions, especially if the goal is to participate in cultural or social conversations 🌍.

Ready to take the next step in your influencer marketing strategy?🚀

Each platform brings something distinct. Each creator has their way of influencing. But all collaborations must answer the same question:

What does this bring to my brand and business strategy? 🤔💡

At Making Science, we have been helping brands evolve in this terrain for years. We design influencer marketing strategies that integrate content, media, and measurement within the digital ecosystem, always with a business focus.

If your brand is ready to move from content to impact, and from punctual impulse to sustained strategy, let’s talk!📧

In today’s crowded digital marketplace, e-commerce businesses face a relentless challenge: standing out and converting browsers into loyal buyers. Generic, one-size-fits-all approaches simply don’t cut it anymore. Customers expect experiences tailored specifically to them. This is where Salesforce Personalization unlocks a powerful advantage, transforming how online retailers connect with their audience and directly leading to a significant boost in e-commerce sales.

Why Personalization is No Longer Optional for E-commerce

Think about your own online shopping habits. Are you more likely to buy from a store that remembers your preferences, suggests products you genuinely might like, or sends you offers relevant to your past purchases? Chances are, the answer is yes. In fact, studies consistently show that consumers prefer personalized experiences and are more likely to convert when they receive them. Without personalization, e-commerce businesses risk losing customers to competitors who offer a more relevant and engaging journey.

How Salesforce Personalization Fuels Sales Growth

Salesforce Personalization isn’t just about adding a customer’s name to an email. It’s a sophisticated platform that uses data and artificial intelligence to understand individual customer behavior and deliver truly unique experiences across every touchpoint. Here’s how it drives sales:

• Real-time Behavioral Insights: Salesforce Personalization continuously collects and analyzes customer interactions on your website, app, and other channels. It understands what products they view, what they add to their cart, what they click on, and even how long they linger on a page. This real-time understanding allows for immediate, relevant responses.
• Dynamic Product Recommendations: Based on individual Browse history, purchase patterns, and even the behavior of similar customers, the platform can display highly relevant product recommendations. This could be “customers who bought this also bought…” or “you might like this based on your recent views,” significantly increasing the likelihood of an impulse or add-on purchase.
• Personalized Website Experiences: Imagine a homepage that changes for each visitor, highlighting products they’ve shown interest in, or promotions relevant to their past interactions. Salesforce Personalization can dynamically adjust content, banners, and even navigation paths to create a unique and highly engaging Browse experience.
• Tailored Email and Mobile Campaigns: Moving beyond generic newsletters, Salesforce Personalization enables segmented and individualized email campaigns. This means sending abandoned cart reminders with relevant product suggestions, personalized sale alerts, or follow-up emails based on recent purchases, all designed to encourage conversion.
• Optimized Offers and Promotions: By understanding a customer’s value and preferences, businesses can deliver targeted discounts and promotions that are more likely to resonate and drive a purchase, avoiding wasted marketing spend on irrelevant offers.

The Tangible Impact on Your Bottom Line

The direct result of implementing Salesforce Personalization is clear:

• Higher Conversion Rates: When product suggestions are relevant and experiences are tailored, customers are far more likely to complete a purchase.
• Increased Average Order Value (AOV): Effective recommendations encourage customers to add more items to their cart, boosting the overall value of each transaction.
• Enhanced Customer Loyalty: A personalized experience makes customers feel valued and understood, fostering stronger relationships, encouraging repeat purchases, and turning one-time buyers into lifelong advocates.
• Reduced Cart Abandonment: Timely, personalized reminders and incentives can bring customers back to complete their purchases, recovering potentially lost sales.

The Bottom Line

In the competitive e-commerce landscape, personalization is no longer a luxury; it’s a strategic imperative for sustainable growth. Salesforce Personalization provides the tools to understand your customers deeply and engage with them on a truly individual level, directly translating into higher conversion rates, increased sales, and a stronger, more loyal customer base.

Are you tapping into the full potential of your digital data or just scratching the surface? Google Analytics 4 is here to change the rules of the game… but only if you know how to play.

📍 Introduction

Since its launch, Google Analytics 4 (GA4) has positioned itself as the new standard in digital analytics. But what makes it so special? And why are so many companies looking for Data Analyst profiles specialized in GA4?

In this post, we explore what GA4 is, why it has replaced Universal Analytics, what this change implies for your company, and how an analyst can turn data into real growth. If you manage digital channels, ecommerce, paid media or UX, then read on.

💡 Fun fact: according to Google, more than 50% of companies that have migrated to GA4 are still not properly exploiting their data due to a lack of analysts or advanced configuration.

🎯 What makes GA4 different?

1. It measures people, not just sessions

GA4 focuses on the user, not on visits. This allows you to analyze the real journey of your customers across channels, devices and platforms.

It no longer matters how many users visited your site, but who they are and what they do.

2. Personalized events: you decide what matters

No more measuring only page views. In GA4 you can track specific interactions: clicks, forms, scrolls, downloads etc. And the best part: everything is flexible, without depending on your IT team at every step.

3. Predictive models within everyone’s reach

GA4 gives you predictions such as conversion or abandonment probability, so you can prioritize actions based on data, not assumptions.

🧠 What if you knew which users are about to stop shopping… before they do?

4. Goodbye cookies, hello privacy

GA4 complies with regulations such as GDPR and adapts without cookies, which is key if your company wants to continue to scale without penalties.

👨‍💻 Why do you need a Data Analyst with GA4 experience?

It is simple: because having data is not the same as understanding it. Let alone acting on it.

✔️ An analyst turns data into decisions

• Configures relevant events and conversions
• Detects opportunities and problems before anyone else
• Relates data to business: sales, leads, profitability

✔️ Able to design useful dashboards for each team

A good analyst doesn’t just extract data, he translates it for Marketing, Product or C-Level. The result? Aligned teams and faster decisions.

✔️ Automate, predict and scale

With GA4 and BigQuery, your Data Analyst can build attribution models, automated reports, or identify hidden patterns that make (or lose) you money.

📌 Raw data is just noise. Advanced analytics turns it into music for your business.

🔚 Conclusion 

Google Analytics 4 has redefined how we measure and understand the digital experience.
However, to take advantage of its full potential, you need a Data Analyst who knows how to extract it, customize it and align it with your business strategy.

At Making Science, we help companies like yours turn analytics into impact. If you’re ready to transform your data into decisions, it’s time to take the next step.

🎯 Do you already have the person to turn your GA4 into a growth engine?

Did you find this article useful?
Share it, leave us a comment, or message us to show you how we work with advanced analytics at Making Science!

Because data doesn’t change your business. The decisions you make with it do.

Let’s face it: eCommerce is competitive. That’s why data is your most valuable asset.

But it’s not just about collecting data; it’s about understanding it and using it to drive growth. Google Analytics 4 (GA4), with its event-driven structure, empowers you to gain much deeper insights into customer behavior. Tracking key events is essential for unlocking the full potential of your online store.

GA4 and the Power of Events

GA4 differs from its predecessor, Universal Analytics, by focusing on events. Every user interaction, from a simple page view to a complex transaction, is captured as an event. This allows for a more flexible and detailed analysis of the customer journey, providing eCommerce businesses with unprecedented visibility into how users interact with their online stores.

How GA4 Key Events Drive eCommerce Success

Tracking these events enables you to:

• Pinpoint Conversion Funnel Bottlenecks: Analyze user flow across events to identify drop-off points. A significant drop between begin_checkout and purchase suggests checkout friction. You can then investigate and address common issues like:
  • Complex or lengthy forms
  • Hidden or unexpected shipping costs
  • Limited payment options
  • Lack of trust or security indicators
• Optimize the User Experience: Event data shows how users interact with your site. Use insights to improve navigation, streamline checkout, and enhance product pages. For example, if users frequently abandon the cart after adding a specific product, you can analyze the product page to see if information is missing or unclear.
• Personalize Marketing and Retargeting: Create audiences based on event activity. Retarget cart abandoners with tailored ads or offers. GA4’s audience features allow you to segment users based on their interactions, enabling you to deliver more relevant and effective marketing messages.
• Maximize Marketing Spend and ROI: Understand which products and campaigns drive conversions. Allocate your budget to high-performing areas and optimize or eliminate underperforming ones. By tracking events related to marketing campaigns, you can measure the effectiveness of your advertising and make data-driven decisions about where to invest your resources.
• Segment and Understand Your Best Customers: GA4 allows you to segment users based on purchase behavior and other criteria. Identify high-value customers and analyze what drives their loyalty. Use this information to refine your acquisition strategies and attract similar buyers.

In the competitive eCommerce landscape, understanding customer behavior is essential for growth. GA4 key event tracking provides the data you need to optimize your store, personalize marketing, and drive revenue. Start tracking these events to unlock your eCommerce potential. If you’re not leveraging these insights, now is the time to start.

Reach out today to get in touch with a Making Science expert to learn more about how we can help you utilize the power of GA4 Key Events.

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We are in the era with digital marketing on top of the world, and looking for the right tools & solutions to excel in your company’s presence is essential. With Google’s Display & Video 360, businesses can reach their target audience with compelling and intriguing still image and video content that drives positive events such as conversions, subscriptions, or whatever your team is reaching to achieve. Let’s look closer into DV360 and the rising question of user privacy within this impactful tool.

So, what is DV360?

Display & Video 360 is Google’s integrated tool for managing programmatic ad campaigns. It’s part of the Google Marketing Platform and offers comprehensive features for planning, executing, and optimizing display and video advertising across various channels. It offers robust analytics and real-time optimization features, making it a powerful choice for advertisers looking to maximize their reach and performance. The impactful feature of enhanced automation helps maintain performance using an advanced AI prediction model to curate an advanced optimization algorithm for your campaigns. Enhanced automation has led to a 60% median decrease in cost per acquisition* in most cases. When it comes to successful verticals, retail, travel, and automotive sectors often see strong performance with DV360 due to its precise targeting and rich media capabilities. What’s unique about DV360, however, is its versatility. DV360’s flexible formatting and diverse content inventory makes it an effective tool across many verticals.

Protecting User Data with DV360

In the year 2024, everyone has seen some case and situation of user data being exposed, which is why 4 of every 5 online users** are worried about their privacy and how easily their data can be stolen. At the same time, 66% of the general population** is still expecting to have a unique, personalized ad experience, which leads to the complications of exposing their data. So, how does DV360 & Google come into the picture and please both parties?

Google continuously updates its practices to ensure user data is protected while maintaining ad effectiveness. Their efforts to continue to preserve user privacy while maintaining a personalized ad experience has been labeled the Privacy Sandbox Initiative. The Privacy Sandbox is Google’s initiative to develop new web standards that prioritize user privacy while allowing targeted advertising. For DV360, this means evolving to use these new technologies, like Federated Learning of Cohorts (FLoC), which should positively impact its ability to deliver personalized ads while respecting privacy. Overall, the changes brought by the Privacy Sandbox should positively impact DV360. While there will be an adjustment period, the move towards more privacy-focused advertising will ultimately build greater trust with users and ensure long-term sustainability for the platform.

DV360 will stay on top

Google’s Display & Video 360 tool is here to stay atop of the digital marketing landscape when it comes to video and image campaigns. Their expansive inventory and capabilities to be activated on almost any platform thanks to Google makes it a top choice for advertisers.

As Google Marketing Platform resellers at Making Science, we are prepared to help deliver the best results for businesses to grow to their fullest potential. Reach out to us today to learn more about our services regarding DV360 and other GMP tools.

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*Source: Google, DV360 & CM360 3P Cookie Deprecation Holistic Readiness Guide, 2023

**Source: Google, DV360: Level Up Webinar, 2024

In the constantly evolving digital landscape, data analysis plays a crucial role in understanding user behavior, optimizing business strategies, and providing personalized experiences. Google Analytics 4 (GA4) is a revolutionary analytics platform that gives businesses advanced insights and a comprehensive understanding of their audience.

GA4 represents a paradigm shift in the field of data analysis, offering businesses a range of powerful features. Its unified data model, multi-platform tracking capabilities, machine learning-based insights, simplified analysis, and reporting, as well as powerful audience segmentation, make it a formidable tool for businesses seeking to fully understand their audience and optimize their digital strategies.

Here are some of the benefits of GA4:

Unified data model and event-based approach

GA4 presents a unified data model that goes beyond traditional page view tracking and focuses on events. With this event-focused approach, businesses can collect data from different touchpoints, such as app installations, in-app actions, interactions with the website, and many more. This provides a global view of user engagement. This unified data model eliminates the need for multiple tracking codes, simplifying implementation and enabling businesses to obtain information across different platforms seamlessly.

Enhanced analysis of the user journey

Understanding user behavior and their journey across multiple devices and platforms has become more complex in today’s interconnected world. GA4 tackles this challenge by offering improved multi-platform tracking capabilities. By unifying data from websites and apps, it enables businesses to track users as they move from one device to another, thus developing a complete understanding of the customer journey. This feature allows businesses to optimize marketing efforts, identify conversion paths, and provide consistent experiences across different touchpoints.

Machine Learning-based insights

GA4 leverages the power of machine learning to provide valuable insights that go beyond basic metrics. GA4 enables businesses to discover hidden patterns, identify audience segments, and predict user behavior by applying advanced analysis techniques, such as predictive modeling and clustering. This AI-based approach helps businesses make data-driven decisions, personalize marketing campaigns, and optimize their websites or apps to enhance user experience.

Simplified analysis and reporting

GA4 simplifies data analysis and report creation thanks to an intuitive interface and user-friendly reporting tools. The platform offers predefined templates and customized reports allowing businesses to visualize data, monitor key indicators, and track performance. The advanced exploration feature allows for in-depth analysis, enabling businesses to discover the information they need quickly. Plus, GA4’s integration with Google BigQuery facilitates the export of raw data for deeper analysis, meeting the needs of data-savvy organizations.

Powerful audience segmentation

GA4’s audiences offer more targeted segments for marketing campaigns. In the new version, GA4 allows you to create segments based on events and time. You can thus group your users based on interactions and the time elapsed between events rather than based on arbitrary device or platform categories. By focusing on these more powerful metrics, marketers can create precise audiences. They paint a valuable picture of your website users and how they engage with content. This creates endless opportunities to optimize conversions and sales.

Making Science is a Google partner; we rely on their tools as well as the power of the Google Analytics platform. From July 1, 2023, standard properties of Universal Analytics (UA) will stop processing data and will be replaced by Google Analytics 4 (GA4).
If you have not already done so, switch to GA4 now, it’s important!

Adopting GA4 drives businesses towards data-driven success in an increasingly competitive digital landscape… Join the GA4 revolution with us today!

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Customers demand experiences where they are treated as unique individuals. And, they want to engage with brands, products, and entities that understand and empathize with their realities and daily challenges.

It’s a reality that the numbers confirm:

• 71% of customers express frustration when their experience with a product or service, from first contact to acquisition, isn’t personalized.
• 80% of customers consider the experience a company provides as important as the product or service itself.
• 64% of the time, a customer switches brands due to the former’s lack of relevance to their behavior.
• 67% of consumers would pay more for a superior brand experience.
• Entities with even a minimally personalized strategy can achieve a 33% increase in customer loyalty.

How to meet this customer need?

Simple! By providing unique experiences to our customers: hyper-personalized experiences. Increasing consumer expectations, parity among products, and prices have prompted the personalization of the user experience (CX) to reach new heights.

Hyper-personalization relies on data, advanced analytics, and artificial intelligence, offering insights and new scenarios where interactions can be tailored to customers’ realities to better meet their expectations. Today, an optimal CX relies on hyper-personalizing all brand interactions, from e-commerce platforms to after-sales service.

In the physical world, hyper-personalization is the unique and personalized attention each customer receives. In digital channels, according to McKinsey, “brands must meet a new standard: the care of one, where all decisions the brand makes aim to cater to each customer and their unique needs independently.”

Advances in technology now allow brands to transform their operating models while reducing CX costs.

To maintain competitiveness in the current consumption scenario, brands must adopt hyper-personalization in their marketing strategies by exploiting data and using advanced analytics and artificial intelligence, all applied in their customers’ journeys to improve their CX and consequently their engagement.

What does a hyper-personalization strategy achieve?

• Increases conversion: By offering customers products, services, or content that are of genuine interest to them, a brand significantly enhances its conversion rates.
• Improves customer loyalty: A well-implemented hyper-personalized strategy makes the customer feel valued and understood, which in turn fosters their commitment to the brand.
• Reduces customer churn: When a customer feels their needs are being met and expectations surpassed, they’re less likely to switch to a competing brand.
• Enhances the brand’s reputation: Customers who enjoy a personalized experience are more likely to recommend the brand to others, which helps to boost its reputation and expand its reach.

Implementing hyper-personalization as a core component of a brand’s strategy can seem overwhelming, but the investment in time, resources, and technology can reap significant benefits in the long run. As consumers continue to demand personalized experiences, brands must rise to the challenge and provide the level of service that keeps their customers coming back.

Remember, successful hyper-personalization isn’t just about using data and technology, it’s also about understanding and respecting each customer’s unique journey and meeting them where they are. By doing this, brands can create truly meaningful connections that result in long-term, loyal customer relationships.

What does a hyper-personalization project look like?

A hyper-personalization project is a continuous process, with information and insights gathered fueling each phase of the methodology.

The methodology of such a project passes through 3 stages:

1. Emotional: We understand how our customers relate to us, contextualize, and understand all the technical aspects and assets that participate in the user experience.
2. Intelligent: This stage determines how we will identify our customers in different digital assets thanks to deep data analysis. By applying machine learning processes to this step, we can integrate all the insights obtained from our customers and exploit them in real time during future interactions with them.
3. Activation: Various hyper-personalized experiments are deployed with the help of artificial intelligence, which allows us to sift through user data in real time and thus provide an immediate response to each of them and their needs, eliminating possible barriers in their journey.

Any hyper-personalization project should allow us to measure our actions so that they serve as a learning opportunity within the project itself.

It’s not enough to just collect data about our current or potential customers and segment them based on that data, as was the case in the past. We need to activate the data.

Data activation involves exploiting our customer data through insights and, at the same time, converting these insights into actionable measures: getting a complete view of the user to improve their experience across all channels and interactions with the brand or product.

What does data activation consist of?

1. Collection: Gather data from any point and transfer it to a centralized platform where it can be aggregated in real-time.
2. Exploitation: Analyze the data to understand its true value and apply it to marketing actions.
3. Hyper-personalization: This is the most complex stage and involves integrating all the data into a common environment where actions can be developed to efficiently link users with a brand or product and thus achieve better performance.

At Making Science, we offer end-to-end content deployments for brands and entities, allowing them to provide unique browsing experiences, just like their consumers. Get in touch with our team today to learn how you can use data to hyper-personalize your customer journeys.

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GA4 is now the present of Analytics, emphasizing full implementation. But, what about the Universal Analytics work and data? Both Google and we ensure you won’t lose your Universal Analytics historical data.

UA will sunset in July 2023, but Google allows data export till year-end. Also, the sunset for Universal Analytics 360 accounts is postponed to July 2024.

How to handle Universal Analytics data?

360 Users should act promptly despite the extended sunset. We at Making Science offer a solution to export and enhance data processing via BigQuery, a pivotal tool in GA4. Linking both will elevate your digital asset data processing. This is applicable only for Universal Analytics 360 accounts.

What if I don’t have a 360 account? Can I still recover my Universal Analytics data?

Non-360 account holders, there are solutions for accounts without BigQuery access. At Making Science, we can assist with data export even without a Cloud account, as per these Google Support articles:

• Export and Share Reports
• Use Google Analytics Reporting API to Export Data

For the 360 users, here’s our solution; BigQuery export.

Requirements for Data Export to BigQuery?

Start by creating a Cloud account, if you don’t have one. Don’t worry, we can set it up for you. To simplify the process, we’ll handle all the necessary configuration on both platforms. Be aware, in BigQuery certain permissions and configurations need to be in place for Universal Analytics to send data to Cloud. This includes specific export settings. Rest assured, we manage all.
This solution stands out as it extracts all historical data automatically, unlike other manual solutions. With BigQuery, you don’t need to select data or reports to export, as all your Universal Analytics history will be stored in the cloud.

Note, BigQuery charges for storage, but these costs are manageable, given the significance of preserving Universal Analytics data.

How can I view my Universal Analytics data?

BigQuery’s role in digital analysis is growing, hence Google now connects BigQuery with GA4 for free and 360 accounts. This means BigQuery unifies Universal Analytics history with GA4 data, displayed in a Looker Studio dashboard. Check this article for linking GA4 with BigQuery to generate Looker Studio reports, conserving quota.

Benefits of BigQuery Export?

Let’s delve deeper into BigQuery export benefits:

1. Preserve historical data: Linking BigQuery with UA ensures all historical data remains intact.
2. Data unification: BigQuery’s GA4 connection allows combining historical and new GA4 data for improved comparison and comprehensive reports.
3. Automated process: Data export is fully automated, eliminating manual exports or other forms of automation.
4. Enhanced data processing and visualization: With BigQuery and Looker Studio, data processing and visualization surpass UA capabilities.

At Making Science, we provide guidance and solutions for any challenges. Our proposed solution for the Universal Analytics sunset is BigQuery data export, which helps maintain, process, and visualize your data. Don’t hesitate to contact us for assistance with this or any other issue. We’re here to help!
Remember, prepare for the sunset—don’t get caught unready!

Predictive Analytics, Machine Learning, Data Science, and Marketing are terms that we hear more and more. This reflects the idea that technology drives marketing to deliver better results and gives it the power to optimize and automate.

With this in mind, traditional marketing data analysis constantly evolves, and we are now in a more advanced stage where technology, along with marketing, stands as a key element to provide calculation, tracking, and prediction that was previously unattainable. In other words, Advanced Marketing Analytics (AMA), the fusion of technology and marketing, has arrived to help us optimize, predict, and better analyze our digital activity.

Advanced Marketing Analytics helps marketing specialists automate and optimize an increasing number of marketing decisions and processes.

Relying on statistical techniques and machine learning models, we can detect patterns and relationships within our data to predict consumer behavior and optimize our activity. Leveraging cloud technologies from major tech partners such as Google Cloud, we always personalize the message or content based on the user’s preferences or needs.

But, how do we get started in the world of Advanced Marketing Analytics? What are its advantages? How can we include this in our own projects?

First of all, we need to clean our data, which must be vast and diverse, to use Advanced Marketing Analytics techniques. Our results will only be as good as the data we provide.

Once this preliminary step is completed, we can use different techniques depending on the case. Here are the most current ones:

Customer Lifetime Value

Predicting a list of users with a propensity to buy can be crucial for our business. However, determining which leads are the most valuable will help even more. The goal is to predict a customer’s expected Customer Lifetime Value based on a brief transaction history. This helps you minimize spend on unprofitable customers, optimize acquisition channels, and reactivate customers with a high probability of being profitable.

Marketing Attribution

Attribution enables us to identify the most effective channels within the customer journey, and using reliable data, we can allocate more or less investment accordingly. This approach optimizes our budget and strategy, focusing on the channels that resonate with our customers and drive conversions.

Clustering

Segmenting prospects and customers into clusters or groups with similarities among them (due to their activity) can help us differentiate the messages we send according to the group. Once these clusters are identified, automated communications should be sent so that the messages vary depending on the group, promoting conversion.

Conversion Prediction

Identifying users with characteristics or behavior indicating a high probability of conversion can help us improve profit margins, as we can direct the right message to users with a higher propensity to buy. Factors like age, gender, location, or device type can help us detect these users. This technique can also identify which factors have the greatest impact on conversion.

Anomaly Detection

Real-time marketing can cause anomalies to appear unpredictably, requiring constant attention to all campaigns and activities. Real-time anomaly detection technology can be crucial for business, allowing us to react quickly and fix the issue affecting our activity.

Forecasting

By analyzing the historical data we have, we can predict trends or anomalies that may affect us in the future, allowing us to react in time and avoid them. When it comes to marketing campaigns, this technique can help us adjust certain parameters to achieve better benefits.

Maximizing Results with AMA Techniques

Thanks to these Advanced Marketing Analytics techniques, we can activate the data collected by our company. Then, we can improve and optimize both budget and processes while achieving greater benefits.

Implementing these techniques was quite difficult in the past, but now there are different technological solutions in the market to carry them out. However, an important point is the prior knowledge and research of these techniques and their needs, so as not to rely on unsuitable tools that end up not helping us solve our business problems.

At Making Science, we have extensive experience implementing these techniques for a multitude of clients, each with completely different requirements and objectives, but always with the common thread of betting on technology to improve marketing activity.

If you are interested in implementing any of these techniques, don’t hesitate to discuss your case with us get in touch by clicking the button below. Or, check out this article to learn about workshops run by Google to help improve your results.

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