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<Img
img="/uploads/trends_in_cdp_2024_bb8e8dcdff.png"
alt="Trends for 2024 in Customer Data Platform"
/>

In the modern world, user data lies at the core of innovative tools rapidly advancing and benefiting businesses. Guided by established customer behavior models and real-time insights, companies make strategic decisions, outpacing their competitors.

This happens for companies equipped with the right software aiding them in achieving data management goals and enhancing the customer experience. Is there a single solution for these tasks? Yes, there is - it's a specialized Customer Data Platform (CDP).

By 2026, the CDP market [**is expected to exceed $5.7 billion**](https://www.idc.com/getdoc.jsp?containerId=prAP50581323), doubling global data volumes.

As more resources flow into customer data, the demand for privacy, neural network capabilities, flexible management processes, and automation will rise.

## Five Key Trends in CDP Development

[**Data management platforms**](https://altcraft.com/en) have been rapidly evolving, particularly in recent years. As brands aim to better understand and efficiently engage with their customers, an increasing number of companies are turning to CDP technologies for data collection, integration, and management to create unified customer profiles. Such profiles are essential for personalizing marketing campaigns and enhancing the consumer experience.

CDPs enhance data structure and organization without the need for a complete overhaul of existing customer support systems. Businesses leveraging AI or machine learning in their operations require a reliable CDP for seamless functionality.

In 2024, several prevailing trends stand out in the CDP market.

### 1. CDPs leveraging neural networks

[**Artificial intelligence**](https://altcraft.com/blog/neural-networks-in-business-marketing-and-life) is transforming every industry, and the CDP industry is no exception. This trend is expected to continue in the near future, with machine learning algorithms becoming commonplace for data analysis, scenario creation, and planning that influence marketing strategies.

For instance, neural networks will be utilized to analyze human behavior and forecast future purchasing trends. This information will then be applied in targeted marketing strategies.

The Altcraft Platform's CDP includes [**an ML module**](https://altcraft.com/blog/altcraft-platform-updates-machine-learning-new-reports-whatsapp) called “Best Send Time.” This function aims to enhance customer service quality through a self-learning algorithm analyzing buyer behavior to determine the optimal time for sending an email to a specific subscriber. This increases the likelihood of the recipient opening the email. Predictive analytics significantly boosts marketing efficiency.

<Img
img="/uploads/best_send_time_altcraft_be3c6fa00e.png"
alt="Send Time within Altcraft"
src="Best Send Time within Altcraft Platform"
/>

Improving service efficiency through ML is a recent trend. For instance, in June 2023, Figma released a major software update. Alongside various enhancements, Figma introduced an artificial intelligence plugin enabling users to tackle tasks like generating icons on demand, creating diverse interface element variations, and modifying information within them.

<Img
img="/uploads/on_demand_icon_generation_281520c433.png"
alt="On-demand icon generation"
src="Example of on-demand icon generation"
/>

<Img
img="/uploads/on_demand_interface_generation_76f204bba3.jpg"
alt="On-demand interface generation"
src="Example of on-demand interface generation"
/>

### 2. Enhanced focus on user data protection

[**Data protection laws**](https://altcraft.com/blog/customer-data-privacy-issues-in-digital-marketing) are tightening, prompting audits to identify breaches in data collection, storage, and utilization by companies.

By 2024, CDPs are expected to prioritize data protection more rigorously. Platform providers must ensure compliance with legislation, and transparency regarding the collection, storage, and use of customer data is crucial.

### 3. Real-time data processing

One of the significant advantages of CDPs is aggregating customer data from various sources to create [**a unified customer profile**](https://altcraft.com/en/features/cdp). However, this process is time-consuming, and the obtained data may lag behind real-time information.

<Img
img="/uploads/customer_profile_in_altcraft_platform_d7720fb7ee.png"
alt="Profile in Altcraft Platform"
src="Unified customer profile in Altcraft Platform"
/>

This challenge is tackled through the development of CDPs that collect and process information in real-time, enabling businesses to make quicker managerial decisions based on up-to-date data. CDPs analyzing customer behavior online, like Altcraft Platform, gather and analyze data immediately upon receipt.

The CDP Altcraft Platform provides detailed analytical reports, allowing for campaign effectiveness tracking and informed decision-making. These include:

- Channel reports

- Traffic reports

- Goal reports

- Sales funnel

- Click map

- Return reports

- Undelivered message reports

- LTV (Lifetime Value) reports

- Audience growth reports

- Cohort analysis

<Img
img="/uploads/channel_report_in_altcraft_platform_9ab35b1279.png"
alt="Channel report in Altcraft Platform"
src="Example of a channel report in Altcraft Platform"
/>

<Img
img="/uploads/traffic_report_in_altcraft_b2f024a43e.png"
alt="Traffic report in Altcraft Platform"
src="Example of traffic report in Altcraft Platform"
/>

### 4. Demand for multichannel capabilities will continue to rise

Today, consumers engage with companies across multiple channels, including email, social media, and [**messengers**](https://altcraft.com/en/features/messengers). Consequently, to meet customer expectations, companies must ensure consistent interaction across all touchpoints.

This anticipates a surge in demand for CDPs with multichannel capabilities, such as [**the omnichannel CDP Altcraft Platform**](https://altcraft.com/en/features/omni-channel-marketing). It aggregates and integrates customer data from various channels to develop personalized marketing strategies and enhance customer service quality.

<Img
img="/uploads/channels_of_interaction_with_customers_81cf2f76ae.png"
alt="Channels of interaction with customers"
src="Channels of interaction with customers on Altcraft Platform"
/>

### 5. Priority on integrating CDP with various marketing services

In recent years, marketing automation platforms have rapidly advanced, aiding companies in [**automating marketing operations**](https://altcraft.com/blog/what-is-marketing-automation-and-how-it-affects-business-development) and personalizing strategies, with customer data utilization being a primary focus.

As a result, by 2024, integration between CDP and various marketing platforms will become inevitable. This will enable companies to leverage all customer data for developing more [**personalized**](https://altcraft.com/glossary/personalization-what-it-is-and-why-personalized-marketing-matters) and effective marketing campaigns.

<Img
img="/uploads/integration_with_other_services_ca6fa86a6d.png"
alt="Integration with other services"
src="Integration of CDP Altcraft Platform with other services"
/>

## Conclusion

Are you harnessing the benefits of customer data? Most modern CDPs come equipped with robust [**analytical systems**](https://altcraft.com/en/features/analytics) capable of storing, enriching, and analyzing data for profit generation. Unfortunately, many users are unaware of these capabilities. Currently, 59% of marketers primarily use CDPs as simple data collection and storage tools.

It's time to think bigger: CDPs are crucial in creating a unified data ecosystem, extracting insights, and implementing data-driven strategies.

Primary source: [**Lytics**](https://www.lytics.com/blog/privacy-agility-and-ai-emerging-cdp-trends-for-2024/)

*products of Meta, a recognised extremist organisation in the Russian Federation

CDPs evolve for better marketing strategies. Trends: AI-driven analysis, data protection, real-time processing, multichannel capabilities and more. 

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In this article about what trends in the field of CDP should be paid attention to in 2024.

Trends for 2024 in Customer Data Platform Development

Key Trends in CDP Development in 2024

<Img
img="/uploads/dannye_o_klientah_dlya_ml_64932f15a2.png"
alt="Machine Learning: How to Use Data Infrastructure for It"
/>

Machine learning (ML) is becoming increasingly important, and those who quickly grasp the functionality of ML will gain an advantage over their competitors. Many companies of varying sizes use purchased technologies to develop marketing strategies, but not all market players accurately assess the suitability of their databases for ML.

Progress does not stand still: companies will be able to derive real benefits from machine learning technology if they learn to collect high-quality source data. The quality of input information directly affects the results of ML.

## How to unlock the full potential of machine learning

To ensure that machine learning models function effectively, it is crucial to load them with a large amount of data. The more comprehensive the information you provide, the more productive the results from machine learning will be. Incorrect or contradictory data can lead to inaccurate predictions by the models.

The accuracy of predictions is important for making informed managerial decisions. "Good data" reduces the risk of errors.

Machine learning algorithms rely on the information they are provided to continue learning and improving. Information is also necessary for adapting the model to new conditions and predicting events in current realities.

## Terms and definitions in machine learning 

**Machine learning algorithms:** These are code elements designed to explore and analyze incoming data. Algorithms can be appropriately referred to as the "brain" of machine learning.

**Machine learning model:** This is a file that is trained to recognize correlations and patterns. Models are trained based on sets of data using a specified algorithm.

**The learning process in machine learning:** This is an ongoing process of adjusting the model based on incoming information. Training concludes when the model creator is confident in the accuracy of the predictions.

*Facial recognition is a widely used function of machine learning. Models are trained on thousands of photographs for an extended period of time.*

**Training on big data:** This is a branch of machine learning that specializes in processing large volumes of information. Without Big Data, achieving reliable results is challenging.

## Stages of machine learning

Let's suppose ML scenarios may seem standard, but the application of this technology improves the customer experience and enhances [**personalization**](https://altcraft.com/glossary/personalization-what-it-is-and-why-personalized-marketing-matters). Additionally, it improves audience segmentation, enables customer churn prediction, and generates quality analytics. The more data you have, the more accurate the forecasts. Therefore, companies need to choose a reliable customer data management platform to accumulate sufficient information. We recommend [**CDP Altcraft Platform**](https://altcraft.com/en).

<Img
img="/uploads/image1_05d977bfae.png"
alt="Customer digital profile on Altcraft CDP"
src=""
/>

**The first stage** of machine learning is the processing of incoming information. It concludes with obtaining a refined dataset. In this initial stage, it is important to identify relevant sources of information. Then, tools are applied to quickly process, validate, and cleanse large volumes of data.

Otherwise, this stage can be called 'data cleaning,' which takes up a significant amount of time and effort. If the input information is in the wrong format or lacks proper context, the training will be incomplete, and the model will not produce accurate results.

**The second stage** is the processing of test datasets. It is at this step that the time and resources invested in the first stage begin to pay off. Machine learning algorithms come into play, and the information from the previous stage becomes the 'test set.' The sets are constantly changing as the process is iterative. Data analysts carefully monitor the model's response to new tests throughout the process and adjust the accuracy of predictions.

**The third stage** essentially involves testing the machine learning model in real-time. It begins when the model demonstrates reliability in the previous phase.

## The route of data

The data journey involves a chain of data transformations, including the collection and processing of input information using machine learning algorithms to enable the model to make predictions and decisions.

### Step 1: Data collection

Information is collected from various sources such as [**databases**](https://altcraft.com/glossary/everything-about-the-customer-database), pixels, platforms, social networks, etc. It is important to have relevant and reliable information about the problem that the ML model is intended to solve.

Preparing customer data for machine learning is not an easy task. This question becomes particularly acute when multiple sources of information are involved, both external and internal.

For companies, input information includes user activity on the web, data on purchases made, interactions with customer service, and monitoring of customer activity in mobile applications.

The process is further complicated by new regulatory acts (such as [**GDPR**](https://gdpr-info.eu/)) that require companies to obtain prior consent for the use of customers' personal data. Without the users' consent to use their information for machine learning, it cannot be used.

### Step 2: Data standardization

Collected data is useless without standardization: it is converted into a format that can be processed by machine learning algorithms, typically CSV or JSON. It is important for the data to be consistent. Duplicate or outdated information is removed, and missing values are compensated for. Data analysts spend a significant amount of time cleaning and harmonizing "dirty" data.

Event specification involves real-time quality checks on incoming data sets. When a new event occurs, the verification is performed. This ensures the cleanliness and alignment of the information for machine learning purposes.

## Why do we need data infrastructure?

Reliable information is crucial not only for machine learning operations but primarily as a foundation for making informed, [**data-driven management decisions**](https://altcraft.com/blog/data-driven-marketing). Decisions that are not based on data have a high probability of resulting in financial losses.

Customer information is collected and analyzed to improve products according to consumer needs and expectations. In addition to the product itself, channels of promotion and communication with customers are adjusted based on the gathered insights.

A strong information foundation leads businesses to growth and enables the automation of routine tasks. The freed-up time allows employees to focus on developing conceptual solutions. The result is increased workforce efficiency, savings in the marketing budget, and growing company profits.

Importantly, without proper data collection, organization, and management, companies will not be able to comply with [**GDPR**](https://gdpr-info.eu/) and [**CCPA**](https://oag.ca.gov/privacy/ccpa) requirements.

Handle your data intelligently with the help of [**CDP Altcraft Platform**](https://altcraft.com/en). The platform also includes an ML module called Optimal Sending Time. It allows you to determine the best time to send emails, facilitating better customer engagement. This can significantly enhance user involvement with your messages.

Machine learning uses algorithms and data to enable computers to learn and make informed decisions, enhancing business operations and customer experience.

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Discover the power of machine learning: transform your business with data-driven insights and predictive capabilities.

Machine Learning: How to Use Data Infrastructure for It

How to Use Customer Data for Machine Learning

<Img
img="/uploads/alternativy_storonnim_fajlam_cookies_98520ab61e.png"
alt="Alternative tools to third-party cookie"
/> 

Just a few years ago, every marketer relied heavily on [**third-party data**](first-second-and-third-party-data), or cookies from external sources. However, Google's recent decision to cease collecting this information has left marketers searching for new ways to work with customer data. Although they have another year to prepare, 54% of respondents claim to have already taken steps in this direction. According to 85% of those surveyed, their work's effectiveness is directly dependent on cookies, while 77% say that Google's decision has negatively impacted marketing business processes.

## What can replace third-party cookies? 

A recent survey of marketers aimed to identify viable alternatives to third-party cookies. The results showed that the most popular alternatives were targeted social media advertising (mentioned by 55% of respondents) and direct user data collection (54%). Google Topics API was also a popular choice, mentioned by 52% of those surveyed, while 36% saw potential in contextual advertising and universal identifiers. 

<Img
img="/uploads/Grafik_1_0974477339.png"
alt="Cookies alternatives"
/>

Let's take a closer look at each alternative.

## Social media targeting

Love it or hate it, social media platforms offer marketers a powerful set of tools for targeted advertising. Gen Z and millennial consumers, in particular, are highly likely to make purchases through social media, which extends the platforms' influence beyond just communication to sales.

During the period between September and November 2022, 33% of social media users made at least one purchase based on [**influencer recommendations**](what-is-influencer-marketing-how-to-build-strategy). Of these users, 28% placed and paid for their order, without ever leaving the social media site, and 22% engaged with brand representatives via the platform.

<Img
img="/uploads/Grafik_2_a0c0cc4360.png"
alt="Generation Z survey"
/>

## Gathering first-party information

The company gathers users' personal data via its official website, surveys, email, SMS, and CRM systems. This information is utilized to develop the business and tailor offers to individual customers. Some marketers still lack knowledge of their customers' demographic information, making the use of user data especially valuable to them.

## Google Topics API

This is a service that tracks which resources users visit when searching for information on a specific query. Although it is not yet widely used, marketers are beginning to consider it a promising alternative to cookies.

How does it work? For example, if someone frequently visits sports streaming websites, Google algorithms will offer that person as an audience for sports-related ads. The user's privacy is maintained at a high level, and advertisers cannot know which specific pages the person visited. Additionally, users can edit their list of interests in the settings.

## Universal identifiers

These are unique IDs assigned to website visitors, which marketers use to distinguish between individuals on websites. They are a close alternative to third-party cookies, as they have a lot in common in the way they work. However, universal identifiers have several advantages:

* Users can be tracked simultaneously across multiple devices, improving the customer experience and eliminating the risk of data loss.
* Duplicate entries are automatically removed, resulting in a higher quality sample.
* Personal data collected through this method is suitable for targeting while ensuring privacy.

## Contextual advertising

Contextual advertising is a different approach compared to the methods described above, as it allows the placement of the right advertisement at the right time and in the right place, without relying on obtaining [**user data for targeting**](what-is-retargeting). Instead, contextual advertising takes into account the current content on the website or platform where the advertisement will be placed.

For instance, an advertisement for headphones can be displayed in the feed of a music blog, where it is relevant to the content. With contextual advertising, advertisers prioritize the context in which the advertisement will be displayed, rather than relying on past user behavior or personal data.

## Why marketing budgets are growing

After the abolition of third-party cookies, marketers had to urgently change their working strategies. On the one hand, there was an incentive to master new targeting methods, and on the other hand, there was a need to ensure the security of user data.

The requirements for preserving customer data confidentiality have become stricter worldwide. This is mainly what led to the increase in marketing budgets. 71% of marketers claim that marketing expenses have increased.

But not everything is so bad. Of course, businesses will have to allocate additional resources to find a reliable alternative to cookies and to retest and find effective ways to achieve their goals and objectives. However, those who go down this path have every chance of improving familiar business processes.

30% of marketers claim that these events have been beneficial to their business and have had a positive impact on the quality of marketing in their companies.

## Future of data privacy: what to expect

The work of marketers is becoming more difficult as they have to adapt to constantly changing rules for collecting and using personal information about customers. On a legislative level, the [**policy on data privacy is becoming stricter**](customer-data-privacy-issues-in-digital-marketing), and users themselves are questioning how their personal information is being used.

Currently, it is unclear what standards companies will have to work with in the near future. Due to this, many firms are allocating a budget for research and seeking new solutions. The first step is to find alternatives to third-party cookies. Ultimately, those who are adaptive in the dynamically evolving world will win.

Learn about the alternatives marketers are turning to instead of third-party cookies and their effects on budgets.

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For those who are already looking for ways to replace cookies.

What Alternatives to Cookies Are Marketers Exploring

5 Alternative Tools to Third-Party Cookies

<Img
img="/uploads/audit_dannyx_014ad471e9.png"
alt="How to Maximize Your Buisness Decisions with Data Auditing"
/>

The world generates [**2.5 quintillion bytes**](https://explodingtopics.com/blog/big-data-stats) of information every day, with the Big Data market reaching $274 billion in 2022 and the analytics platform market following suit. This upward trend shows no signs of slowing down.

Data is highly valuable for businesses, serving as an inexhaustible source of inspiration for marketers and [**providing insights**](https://martech.org/analytics-audit-101-identify-issues-and-correct-them-to-ensure-the-integrity-of-your-data/) into consumer habits and expectations. Through data, companies can make informed predictions about their growth and select effective methods for outcompeting rivals.

However, processing large amounts of information is a challenge. Without quality analytics, the data collected is nothing more than meaningless numbers.

Data analysis, first and foremost, involves checking the authenticity of the information. But that's not all. The main task of the audit is to determine how the collected data can help the company solve the set tasks. Without accurate data, companies can't make informed decisions. Let's explore data auditing in more detail.

## How data auditing can benefit your business

Data can be a lifesaver for a company, as long as the sheer amount of it doesn't overwhelm management. Storing a large volume of information can be costly, and it needs to be organized and utilized correctly. This is where a data audit comes in. Data auditing can:

- **Consolidate disconnected databases from various departments.** Auditing, using cloud tools, can combine information across the entire company. This allows marketers to utilize valuable information collected by the sales department.
- **Resolve data integrity issues.** Company databases often contain duplicated, incomplete, or incorrect information, which cannot be used as a basis for business decisions. Relevant and reliable data is needed to solve business problems.
- **Comply with regulations.** To maintain order in business processes, many companies establish internal regulations for handling information, while some industries are regulated externally. Auditing helps ensure compliance with prescribed rules, avoiding fines for violations of data storage and usage deadlines.
- **Avoid data leaks.** [**Data leaks**](how-to-respond-to-data-breaches) occur when third parties gain unauthorized access to information that is not intended for them. Personal data security issues can be significant for companies, which is why they are vigilant in this area. Data auditing highlights vulnerable areas.

## Phases of data auditing

### Step 1. Planning

At this stage, it is necessary to develop a step-by-step plan for the audit and assign responsible individuals for its preparation, conduct, and presentation of results. The success of the entire «operation» depends on how well the planning is done.

### Step 2. Inspection and information gathering

Find out what information is currently stored in the company. How it is collected, how long it should be stored, and most importantly, how it is used in business processes.

### Step 3. Analysis and evaluation of data collected

Evaluate the situation for compliance with legislation and regulatory acts. Check data security and determine the procedure for employees' access to information.

### Step 4. Development of recommendations

Develop correct business processes and implement them in practice. Reject and replace non-working algorithms. Provide recommendations to employees on how to work with information. Remove excess data, set current storage periods for information that quickly becomes obsolete. Provide access to information for those employees who need it for their work.

<Img
img="/uploads/data_audit_steps_7cd0afe42d.png"
alt="Phases of data auditing"
/> 

## Who is in charge of data auditing?

Data scientists are usually the ones responsible for conducting data audits. In some cases, it may be appropriate to form a team of competent individuals to monitor information usage, make budget decisions, and set priorities. The team's work typically results in internal policies and data processing strategies that are then shared throughout the organization. This is how employees are trained to work with data within the company.

## Why is data audit automation needed?

Based on the analysis of events of the past three years, it can be confidently stated that customer information quickly becomes outdated: their behavior and desires change so rapidly and unexpectedly. Data quality auditing is necessary for modern businesses, as it provides the opportunity to make relatively accurate predictions of the near future. However, processing large amounts of information manually is practically impossible.

This is where data management automation platforms come in. They completely take over routine and labor-intensive processes such as cleaning the database of duplicates, monitoring information sources, and clearing the database of clutter. All of this is necessary, but it is not practical to do it manually.

Automating data auditing is beneficial for the company. It significantly frees up employees' time that they can spend on more critical and creative tasks. Moreover, the results obtained are more accurate and reliable than if the database were processed by a human. Robots do not make mistakes, do not get distracted, do not tire, and their vision does not «blur». Therefore, in this regard, they work much better than a human.

## How to choose a data audit automation tool

Platforms designed specifically for collecting and storing marketing data can help you with this task. Artificial intelligence has made significant advancements in this area, enabling precise targeting of marketing campaigns and reaching interested audiences.

Smart platforms identify new visitors using JavaScript tags and track their IDs, gradually building detailed profiles that include behavioral characteristics, demographic data, and purchase history. The data is not mixed up between users, processed accurately, and subjected to analysis.

When selecting a platform, it is important to look for the ability to [**segment users into target audiences**](how-and-why-to-segment-target-audience) in real-time. Businesses find it easier to succeed in the market when they have accumulated enough useful information. The key is to ensure that this information is relevant to improving current business processes within the company.

In this post , we will explain what a data quality audit is, how it can help your marketing, and how to conduct a data audit.

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For those who want to know what a data audit is and how to conduct it.

How to Maximize Your Buisness Decisions with Data Auditing

Data Quality Audit: How It Can Benefit Your Marketing

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img="/uploads/chto_takoe_tranzakcionnye_dannye_a27ed47d1a.jpg"
alt="How to use transactional data to grow your business"
/> 

There are many sources of information that can be used to study the target audience and customer behavior. For example, you can track the actions of visitors on the company's website — any data collected will be very valuable. It is better for a business to build marketing campaigns based on the analytics of the accumulated information, because this way the creatives will hit the target.

Transaction information is a type of data that is easy to collect, yet very valuable. In this post, we will explain what transactional data is and how to use it to improve the effectiveness of your marketing.

## What is transactional data

**Transactional data** is any information relating to customer transactions. A transaction in an online store is defined as an "event" during which the user's web browser and the company's website exchange data. What is the difference between transactional data and other data types? It contains the exact date and time of purchase.

<Img
img="/uploads/transactional_email_from_amazon_5a6e29cb70.png"
alt="Amazon transactional email"
/> 

In addition to the date and time of payment, managers get other valuable information: the product or set of products that attracted the customer, the type of payment, the frequency of purchases and the promo codes used. It is also possible to analyze user behavior before and after a purchase.

## How to use transaction data

It is not enough just to gather data — you need to use it in the right way. The value of this information is that it provides businesses with a comprehensive view of customers' online behavior. The company tracks clicks and knows why users drop off the site without making a purchase or [**abandon their shopping carts**](how-to-reduce-cart-abandonment-rate). Analytics gives tips on where business growth points are and how to increase customer loyalty.

The undeniable advantage of transaction data is that it is reliable because it comes from first-party sources — directly from prospects and leads.

## Examples of using different types of transactional data

### Location info

For offline business, information about the "hot spots" of potential buyers has a huge weight. It is taken into account when opening new outlets. But when it comes to online stores, location is just as important. Geography of customers is useful in product planning. Logistics should be thought out more carefully in cases with seasonal goods. For example, you can move goods from regions with low demand to where demand is higher.

### Payment types

The payment type is an important piece of transactional data. Firstly, it is useful for businesses to calculate how much each transaction costs, and what it includes: a commission from a bank or another intermediary. Ultimately, all this affects the profit of the organization.

You need to add all the payment methods demanded by customers in order to grow in sales. The more comfortable the payment process is for customers, the more they are attracted to the company, and the more likely they will make repeat purchases.

<Img
img="/uploads/mango_payment_methods_3811e2c819.png"
alt="Mango payment methods"
/>

Payment information is also used to quickly troubleshoot technical issues. If a company is used to tracking transactional data, it will see and respond to errors in card reading and delays in payment processing in time. All this together will reduce the number of abandoned carts and unsatisfied customers.

### Discounts and promotional codes

This is probably one of the most useful types of transactional data. There is a certain category of people who make purchases only on favorable terms. The analysis of such sales statistics brings the most unexpected insights, on which effective advertising campaigns are built.

You may find that a 10% discount on products has no effect on customer demand, but when a free shipping promotion is running, sales increase. It happens that the same discount, presented with different wording, is perceived by consumers in completely different ways. Let’s compare: “Buy one item and get the second one at half price” and “25% off the entire range of products.”

As for promotional codes, their validity period is limited and the time frame of the offer is precisely known, so you can analyze sales for this period and draw conclusions about the effectiveness of [**using promotional codes in marketing campaigns**](how-to-use-promo-codes-for-business).

<Img
img="/uploads/Screcasper_promo_code_email_b37f087575.png"
alt="Promo code in an email from Casper"
/>

It is important to always compare different types of transactional data with each other. Consider both the location and the payment method, but do not dig into the calculations. Use only the data that you need at the moment.

### User behavior before and after purchase

Everything we talked about above applies directly to the purchase. Time, date and type of purchase are undoubtedly very important transactional data, some of which is captured by the sales platform. Data on customer behavior before and after the purchase is considered to be indirect, but it cannot be classified as secondary. By studying this information, you can answer the following questions:

* How many times did the user view the item before purchasing?
* What products did the customer compare the product with?
* Did they read product reviews?
* How long has it taken the customer to buy the product since they saw the product for the first time? What [**pushed them**](5-marketing-techniques-to-push-customers-to-buy)?

Perhaps the company sent out promotional codes at the time of purchase, and this spurred the consumer to purchase. Answering these questions and analyzing patterns will help you better understand the goals and motives of your target audience.
The deeper you understand customer habits, the more effective your marketing campaigns will be.

### Transactional data makes sales easier

All obstacles to sales must be removed. By tracking transactional data, the company gains insight into the types of payments that often fail, as well as the people who started checkout but didn't complete it. Perhaps there was no convenient option in the list of payment methods, or maybe another problem “scared away” the person.

Profit grows if the company aims to facilitate the sales process in such a way that the client does not encounter any obstacles. This means minimizing the number of clicks, forms to fill out, and eliminating all system errors. Otherwise, the sale will not happen, and the business will miss the customer.

<Img
img="/uploads/mango_checkout_process_0d4a34aa0b.png"
alt="Checkout process on the Mango's website"
/>

## Increase customer loyalty using transactional data 

Transactional data helps personalize offers. Customer loyalty is extremely important for any business, and every opportunity should be taken to maintain it. All information about transactions, even anonymous ones, is useful for these purposes. The company can tailor promotions to the needs of a specific audience if it understands the needs of customers.

Take a closer look at the statistics of purchases of a particular type of products and determine the time that is best for your offer. Let's get back to seasonal items. To free up space in the warehouse for the new collection, you can come up with a promotional offer for the old one. Customers become more active, and you will spend less on moving the old collection to a location with high seasonal demand.

## Marketing automation platforms and transactional data

Companies accumulate terabytes of data every day. It is quite difficult to process such a volume. Information is an asset, and there should be just enough of it to solve a specific business task. The same rule applies to transactional data. When there is a lot of information coming in, companies don't know what to do with it. And even if they know, there is often not enough capacity to process such a volume.

This is where modern marketing automation platforms like the [**CDP Altcraft Platform**](https://altcraft.com) come in. With the right tools, transactional data works for your business.

Transaction information is a type of data that is easy to collect, yet very valuable. Read the post to learn what transactional data is and how to use it.

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For those who are wondering what is the use of transactional data for companies.

How to Use Transactional Data to Grow Your Business

How to Leverage Transactional Data

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The Ponemon Institute has published a report on the financial losses of organizations that occurred as a result of data breaches. The cost of stolen information in 2021 increased by 10% compared to the previous year. The total loss amounted to $4.24 million (against $3.86 million in 2020). Most often, hackers attacked customer personally identifiable information (PII).

Currently, society makes serious demands on businesses when it comes to protecting confidential data. However, breaches do happen. How to detect unauthorized access to information and what should be done in this case? Let’s discuss this in the post.

## What is a data breach

If information falls into the hands of persons for whom it is not intended, they speak of a data breach. Most often, it is official or [**confidential information**](ways-to-address-customer-data-privacy-issues-in-digital-marketing). Hackers steal personal data of employees, credit card numbers of customers, as well as information related to trade secrets.

**Types of data breaches:**

- Information that identifies users: names, phone numbers, emails, physical addresses, and others. 
- Financial data: banking information, credit card numbers, passwords and logins that fraudsters use to steal money from bank accounts.

## Examples of data breaches in companies

Robinhood is an American financial services company. The company has an application through which users invest and trade stocks.

In November 2021, 5 million user emails were stolen from the company. The scammer learned the names of 2 million Robinhood customers and demanded money for non-disclosure of information.

First of all, Robinhood turned to law enforcement with a statement about extortion of money. They then prepared and published an incident report for app users and personally contacted affected customers. The company also signed a long-term contract with Mandiant, a leader in cybersecurity. Mandiant helped Robinhood eliminate the data breach and became responsible for its data security in the future.

Social media platform, Linkedin, suffered a data breach that compromised the personal information of 165 million user accounts. The data breach — which cost the company over three million pounds to clean up — has widely been reported as the result of weak user passwords.

<Img
img="/uploads/kartinka_2_aedead30dc.png"
alt="Social Media: People Still Use Pathetic Passwords"
/>

## How data breaches happen

According to the Verizon 2022 [**Data Breach Investigations Report**](https://www.verizon.com/business/resources/reports/dbir/), the most popular method is criminal hacking. Hackers use phishing, brute-force attacks on data servers, spyware and malware.

Breaches also happen within companies. For example, when an employee accidentally reads information on a colleague's computer without permission. Although the access is unintentional and the "secret" is not shared, such an incident is considered a breach of data security. 

There are also cases when an employee intentionally gains access in order to use the information in bad faith.

## Data breach: red flags

It is time to suspect a data breach if you notice the following signs:

- Company’s confidential data appeared in the public domain (for example, on the Internet).
- Data downloads by unauthorized users were recorded within the corporate network.
- Someone tries to log into the system from suspicious devices.
- There is activity in the corporate network at uncommon times.
- System crashes, password changes and uncontrolled account lockouts are common.
- Payments in e-commerce began to give errors.

## Who to report a data breach

The company must report to the appropriate organization that there has been a data breach. The organization varies depending on the location of the business and its customers. In 50 states of America, the procedure for notifying customers about a data breach incident is legally established.

On the territory of the European Union, the first to know about what happened is the DPA, a special organization responsible for the safety of personal data. The [**GDPR**](customer-data-privacy-issues-in-digital-marketing) requires businesses to notify the DPA within 72 hours.

## Data breach prevention

Now we will talk about how to prevent data breaches from happening, but not about what to do when it has already happened. You should constantly improve your data security to keep your business safe. Here are steps to take:

- **Set up limited access to data.** Let those people who need it have access to information. Do not give access to data to those who do not need it for the quality of their work.
- **Keep the software up to date.** Outdated software contains many security holes through which confidential information can leak out of the company.
- **Take passwords seriously.** If fraudsters find out the password to enter the system, all doors will open for them. We recommend that you change your work passwords every quarter and do not use simple combinations.
- **Protect employees' personal devices.** When the personal equipment of specialists is involved in the workflow, there is a risk for the business. The threat can be leveled with the help of antiviruses and VPN.

## Protect your data with Altcraft Platform

[**Altcraft Platform**](/en) is a reliable marketing automation platform with full data flow control. We take into account all the requirements of customers for the security of information. When requested, the platform can be deployed on the client's server. On Premise hosting enables rapid implementation without sacrificing security. Altcraft Platform has no limits on the amount of information to be stored and on the number of messages sent. There is no need to resort to the help of third-party vendors.

In this post, we talk about what data breaches are, how they happen, what to do, and how to detect and prevent them.

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How to detect unauthorized access to information and what should be done in this case? 

Data Breaches: How Your Business Should Respond to Them

How to Respond to Data Breaches

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img="/uploads/Blog_3d85602fec.png"
alt="8 Ways to Protect Your Customer Data"
/> 

Previously, only one department of the company stood guard over customer data. Now data safety is the business of every employee, since access to information is provided to almost everyone, but to varying degrees. In this post, we will talk about the constant protection of personal information, the consequences of leaks and the components of reliable protection.

## Why data protection is important

When it comes to protecting customer data, it is about protecting personally identifiable information (PII). PII are individual markers of a person: full name, passport details, residential address, contact information (phone, email, social networks), IP address, payment details and social status. This information should be carefully protected from accidental leaks.

Moreover, not only large companies should think about this issue, but also the smallest ones that have any kind of customer database. Ironically, the worst data offenders are conglomerate companies like Yahoo, Amazon, and Google. However, you can't be too careful in this matter.

From **a legal point** of view, failure to comply with PII protection requirements will inevitably lead to fines. Laws vary depending on the scope of the business and territorial affiliation. They are most often tied to the location of the user, not the data processor. For example, it is likely that any digital business will fall under the [**GDPR**](customer-data-privacy-issues-in-digital-marketing) (General Data Protection Regulation for EU citizens).

There are also **reputational risks**. Leaks to third parties can lead to loss of customer loyalty and trust in your company. At best, the business will get a lot of [**negative reviews**](how-to-use-customer-feedback-to-increase-sales) on various resources and a bad reputation in the media, and at worst, it will get a lawsuit, perhaps even a class action lawsuit.

As for **internal business processes**, it is unprofitable for a business to spend extra time (and therefore money) on handling incidents related to the leakage of customer data. Inside the company, it is better to [**build a system**](ways-to-address-customer-data-privacy-issues-in-digital-marketing) for protecting personal information so that it functions reliably almost offline and does not take time from employees.

The most important things are **privacy** and **security**:

- To maintain privacy, take action on information in accordance with the permissions received from users and control access to information.
- To ensure security, you need to have a plan of action to prevent scammers, hackers and untrustworthy employees from accessing confidential information.

## How to get started with data protection

Before you begin to study the components of the security of personal information, try to answer the following questions as honestly as possible:

### Do you have sufficient knowledge of the legal requirements for protecting confidential data in the area of your business?

Not only do the requirements of the legislation vary in different countries and in different areas, but lawmakers are constantly making changes to the set of rules that must be followed.

### Are you sure about the reliability of the third parties whose services you use?

It is likely that your business operates on the basis of third-party services. If they dishonestly dispose of the [**client data**](first-second-and-third-party-data) that you provide to them, the responsibility for what happened will still fall on you. Therefore, carefully choose partners: hosting, CDP, email services, and others.

If you've reviewed your answers to the questions above and come to the conclusion that there's nothing to worry about, it's time to move on to specific steps you can take to secure your client database.

## 8 steps of reliable protection of confidential data

### 1. Define the risks

Good data protection strategies are based on the analysis of risks and threats for the business. If you approach the issue comprehensively and describe in detail all possible threats, you get a full-fledged risk profile. This way, the company will have an idea of the dangers and weaknesses, and it will have time to develop countermeasures. 

### 2. Find a Data Protection Officer (DPO)

Perhaps a small business will find it unnecessary to hire a data protection specialist, but every company should make sure someone is in charge of data protection and security. The specialist is engaged in training and auditing, monitors legislation, and also closely cooperates with regulatory authorities. DPO will also be able to deal with customer requests on data security issues at a higher competent level.

### 3. Store information in one place

The more places where information is stored, the higher the likelihood of leaks. In addition, disparate information is difficult to process and analyze. Most often, such data is not suitable for effective work with them. What’s more, it easily leaks outside the company, gets into unauthorized applications and disappears out of control. The problem is solved by the use of [**Customer Data Platforms**](/features/cdp) (CDP), which combine all information into single client profiles with access to them by a limited number of people.

<Img
img="/uploads/digital_profile_2_e79e5283cc.png"
alt="Customer digital profile"
/>

The CDP traces the history of the data and all associated permissions. This is especially important for businesses that are regulated by GDPR and CCPA laws.

### 4. Collect only the data you need

Extra information will not help you in any way to achieve your goals, and it will soon become outdated, lose its relevance and become unusable. And if this data is leaked, you will be responsible for it. A large amount of information attracts hackers and scammers.

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img="/uploads/tilda_subscription_form_ed2f130145.png"
alt="Opt-In form on a website"
/>

### 5. Limit employees who have access to information

Not every employee in your company needs access to customer information in order to work. Let the information remain at the disposal of only those persons who actually need it for the quality performance of their work duties.

### 6. Choose reliable software

Most modern technology is already equipped with primitive anti-fraud measures. But it is important to make sure that the built-in antiviruses work correctly. Don't rely on them alone. Better install a firewall, use external links, and test the software to see if it flags suspicious emails.

### 7. Develop a contingency plan

Hackers are now progressing and can break even a reliable system. All previous steps were aimed at preventing data leakage: identifying the danger, trying to level it completely, or reduce the negative consequences. If a leak does occur, it's a good idea to have a working emergency plan. At a minimum, you need a good external specialist for expert assistance.

### 8. Train employees

Not all employees need access to personal information, but it is everyone's responsibility to think about the security of work information. You should educate staff about basic data protection practices and how to recognize fraud. In case of violations, employees must immediately inform the competent authorities. Let the issue of safety be included in the onboarding training of newbies.

## Conclusion

Ensuring the safety of confidential customer data is an important business task. The significance of the issue is confirmed both by legislation and reputational aspects. Collect only the data you need. Firstly, users are annoyed when they are asked about all areas of life, and secondly, complete databases are highly valuable and attract scammers and hackers. Take a closer look at the other ways to protect information described in this post. Perhaps one of them will save your business from trouble.

In this post, we talk about why information privacy is important, and how businesses can protect customer data.

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In the digital world, information is an attractive source for hackers, so the safety of data is an important task in business.

How to Protect Your Customer Data: 8 Effective Ways

8 Ways to Protect Your Customer Data

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img="/uploads/How_CD_Ps_Will_Save_Marketing_in_a_Cookie_Free_World_c0c129f31f.png"
alt="How CDPs Will Save Marketing in a Cookie-Free World"
/>

Cookies (third party cookies) have been the lifeblood of online marketing for over a decade. With the help of them, marketers tracked the actions of users on the Internet and made advertising. The company received information about the behavior, preferences and interests of the audience.

But with the advent of GDPR and CCPA, which will close access to third-level data in 2023, marketers are beginning to think more seriously about advertising in [**a privacy-first world**](customer-data-privacy-issues-in-digital-marketing).

Marketers are starting to adapt to a world without cookies and are realizing that CDPs (Customer Data Platforms) are becoming a powerful marketing tool. CDP manages, collects and stores customer data in compliance with data protection regulations.

## What a world without cookies would look like

Imagine what would change on the Internet without cookies.

### Google Topics (and others…)

Topics are the third part of Google's decision to block access to third-party cookies. The tool groups users by unique identifiers: the IP address accessed by the client's web browser. The API stores information about three to five topics with which a person constantly interacts on the Internet. For example, sports, news and pets.

Websites are then able to access these topics to produce advertisements that will possibly attract the user when they visit the site. For example, an ad for pet products appears next to sporting goods.

But that's part of the problem when it comes to new ideas for ad targeting.

In the new reality of targeting, marketers are discussing and testing other methods:

- Contextual targeting 
- Universal Identifiers
- Probabilistic
- Cohort-based targeting 

### First-party data precedence

Because of the rejection of third-party cookies, companies and marketers must make full use of first-party data. This is information that the company collects from customers and becomes the sole "owner". Such data is valuable to marketers because it provides accurate information. Another advantage is the transparency of the provenance. 

Data from customers is important in a world where privacy is a priority. When a business has complete information about the customer's journey, it regulates the use of data without any problems: it selects those to which users themselves have opened access.

With first-party data, marketers have access to a wealth of information such as consumer preferences, location, and other demographic data that can all be used to build a complete [**customer profile**](creating-a-customer-profile). Further, advertising is set up for the user and the company's marketing works. First-party data strategies are able to maintain positive and compliant customer experiences, protect personal information and enhance advertising opportunities for marketers.

### Customer Data Platform Benefit

The creators of Data Management Platforms (DMPs) and Customer Data Platforms (CDPs) were already gearing up for a world without cookies.

According to the latest research by Zeotap, 1% of marketers are ready to abandon DMP and switch to CDP. Why?  It's all about the [**first level data**](first-second-and-third-party-data) that CDP usually uses (as we now know, this is the key to success in a future without cookies). DMP works more often with third-level data.

## 6 ways CDP will solve the problem of a world without cookies

### 1. Data collection management

The gigabytes of data that companies collect across dozens of touchpoints (customer service, websites, point of sale) can reveal the needs and desires of consumers. However, collecting, managing and analyzing data from multiple sources can sometimes be a minefield.

This is where [**CDP**](/features/cdp) comes into play. The CDP is able to collect information, manage first-level client data from unrelated sources and make it usable.The platform unites information into single customer profiles, sometimes referred to as "golden records".

CDP receives this data in an unlimited number of formats: files, integration with other platforms and even web application pixels. A good CDP will pull information from just about anywhere.

### 2. Resolve identities into a single customer view 

A 360-degree customer view, often referred to as a single customer view, is a comprehensive aggregation of available user data.

This information may include contacts, user purchases, details of transactions that customers have made at business touch points (such as customer service or stores) along the customer journey. Customer data comes from different sources.This is a large amount of information that must be aggregated, cleaned and combined. It is then stored in a secure location that is accessible only to interested employees. But with cookies gone, identifying customers and attributing the right data fragments to them gets harder.

Here, Identity Resolution technologies play a decisive role in platforms. They compare, standardize and verify information. The attributes of the same individual user are linked together under a unique ID by applying a classification scheme to the data labels of your multiple sources. It enables the creation of a single view of the client that the business needs.Therefore, customer data platforms are the best software for creating a secure and complete client profile.

### 3.  Manage Consent

CDP tracks and manages the whole consent journey. This is vital to ensure that the customer's data is only handled in the way that the customer has authorized.

For example, a customer consents to the use of personal data for the company's marketing purposes via a [**mobile app**](mobile-app-as-a-marketing-channel), but might later retract that consent when engaging via email.

In unifying that customer’s data from separate channels and data sources, a CDP integrates customer consent records to work with their data. The process is called consent orchestration, which makes it easier for the user to choose.

### 4.  Enable activation in walled gardens 

In the cookieless future, marketers will still want to use the addressability options that will remain in the biggest platforms. These ‘walled gardens’ like TikTok, Facebook and Google Ads, which will take on a new role as the open web adapts to life without cookies.

But there is one thing. Walled gardens mean multiple data sets with multiple activation requirements: a very manual process which can result in delays. Paid media managers know exactly what we're talking about.

If a business needs a data-driven strategy that launches in a couple of clicks, a CDP is the way to go. With a customer data platform, a company gains access to customer segments that are activated across multiple channels with a single click.

There will be no dependence on data collection teams, and the information received will work more efficiently. CDP will help you [**identify segments**](how-and-why-to-segment-target-audience) of possible customers through behavioral data from various touchpoints. 

Therefore, if in the past you created audiences and thought: “I wish I could combine data from our CRM and website”, now you have found the answer.

### 5. Activation across the open web through Universal IDs

In the future, CDP will become the main tool for dealing with addressability on the open web through Universal IDs.

Universal IDs are shared, persistent identifiers that link users across the digital marketing ecosystem. They are needed to ensure the future of identification and addressability when third-party cookies are deprecated in 2023.

The customer data platform will be able to unify the disparate data collected by the business and create a hashed unique universal user identifier. This identifier is transmitted over CDP communication channels and compared with information from data sources (websites or apps).

If identifiers from different channels match in parameters, then they are assigned as a single universal ID for one user. Then you can launch ads for target consumer segments.

### 6. Provided Opted-In Audiences To Publishers

CDP tracks brand touchpoints and marketing preferences so that a business is only advertised to an interested audience when it reaches different segments on the open web.

**Here are benefits of CDP for marketing:**

- Advertising works according to the law. Each opt-out request is automatically tracked and counted across all channels.
- The accuracy of the audience selection, because data is selected from several sources within the business.

In this post, we talk about why CDP is a powerful marketing tool. We also share 6 options for how platforms will solve the problem of a cookie-free world.

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As marketers begin to adapt to a cookie-free world, they are quickly learning that CDPs are becoming a powerful marketing tool.

How CDPs Will Help Businesses in a World Without Cookies

How CDPs Will Save Marketing in a Cookie-Free World

All user information is systematically collected in a unified customer data platform

Distributing messages across various communication channels: email, SMS, push notifications, messengers

Promo codes, bonuses, and points for building long-term customer relationships

You can create and edit any HTML template, as well as save your own custom blocks

Personalized distribution of messages to clients through communication channels

Conducting experiments and optimizing marketing strategies

Tracking the effectiveness of marketing campaigns to make informed decisions

Connecting external systems to the platform and synchronizing data with company databases

Creating questionnaires, surveys, and feedback forms of any level of complexity

The ability to communicate with your clients anytime and anywhere

Customer Data Platform

Omnichannel Marketing

Loyalty programs

HTML Email Builder

Personalized mailings

A/B/n Testing

Real-time analytics

Integration and WebHooks

Forms and Surveys

Messenger Communication

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