In 2021, spending on digital advertising to children stood at *** billion U.S. dollars worldwide. Between 2021 and 2031, it is expected to increase at a compound annual growth rate (CAGR) of roughly ** percent to reach **** billion dollars. Kids digital ad spending data by region reveals that North America (Canada, Mexico, and the United States) was the largest investor in this field, accounting for ** percent of the total, followed by Europe with ** percent, and Asia-Pacific with ** percent.

In 2021, spending on digital advertising to children stood at *** billion U.S. dollars worldwide. North America was the largest market, accounting for ** percent of the total spending or **** billion U.S. dollars. Europe followed with ** percent or *** million dollars.

Between January and November 2023, advertisers part of the baby and kids industry in the United States spent nearly **** billion U.S. dollars on advertising, up from less than **** billion dollars during the first 11 months of 2022. That represents an annual growth of almost ** percent.

According to Cognitive Market Research, the global Kids Digital Advertising market size will be USD 8240 million in 2025. It will expand at a compound annual growth rate (CAGR) of 23.40% from 2025 to 2033.

North America held the major market share for more than 37% of the global revenue with a market size of USD 3048.80 million in 2025 and will grow at a compound annual growth rate (CAGR) of 21.6% from 2025 to 2033.
Europe accounted for a market share of over 29% of the global revenue with a market size of USD 2389.60million.
APAC held a market share of around 24% of the global revenue with a market size of USD 1977.60 million in 2025 and will grow at a compound annual growth rate (CAGR) of 26.5% from 2025 to 2033.
South America has a market share of more than 4% of the global revenue with a market size of USD 313.12 million in 2025 and will grow at a compound annual growth rate (CAGR) of 24.2% from 2025 to 2033.
Middle East had a market share of around 4.00% of the global revenue and was estimated at a market size of USD 329.60 million in 2025 and will grow at a compound annual growth rate (CAGR) of 24.9% from 2025 to 2033.
Africa had a market share of around 2.2% of the global revenue and was estimated at a market size of USD 181.28 million in 2025 and will grow at a compound annual growth rate (CAGR) of 23.7% from 2025 to 2033.
Desktop & Laptops category is the fastest growing segment of the Kids Digital Advertising industry

Market Dynamics of Kids Digital Advertising Market

Key Drivers for Kids Digital Advertising Market

Growing Utilization of Cutting-Edge Digital Marketing Tools to Boost Market Growth

businesses are investing a lot of money in digital marketing since it strengthens their brand, expands their customer base, and increases return on investment (ROI). These days, kids use social media sites like Facebook, Instagram, Snapchat, and educational apps. As a result, targeting children is simple for digital advertising companies. Digital marketing firms employ a range of advertising formats, including broadcast, sponsored search, social media, and display advertising. For instance, According to a parent study conducted in October 2021 by C.S. Mott Children's Hospital, 49% of parents of children aged 10 to 12 reported using social media apps in the previous six months, followed by educational apps (28%), and miscellaneous apps (23%). 32% of parents reported using social media applications, 50% said they used educational apps, and 18% said they used other apps for children ages 7 to 9.

https://mottpoll.org/reports/sharing-too-soon-children-and-social-media-apps

Increasing in Children's Smartphone Adoption and Internet Penetration Boosts The Need For Advanced kids Digital Advertising To Boost Market Growth

In addition to the channels and choices they make, children's extensive usage of technology is having a significant impact on families. The market for digital advertising for children is anticipated to grow as more children acquire smartphones. Additionally, the internet has transformed the world, helping businesses, sectors, and consumers alike. One major factor contributing to the sharp rise in mobile applications is the rise in mobile Internet usage, which is expected to drive the children's digital advertising market over the course of the projected period.

Restraint Factor for the Kids Digital Advertising Market

Parental Concerns About the Effect on Health Of kids Digital Advertising Limit Market Growth, Will Limit Market Growth

The possible harm that digital advertisements may do to children's development, behavior, and mental health is making parents more conscious. Increased scrutiny and opposition to digital advertising aimed at youngsters are the results of this expanding awareness. In order to allay these worries, advertisers need to develop moral and responsible advertising strategies that put the welfare of kids first. Regulations have been put in place by governments and trade associations to guarantee that advertisements are age-appropriate, truthful, and do not take advantage of children's inexperience. These rules restrict the kinds of products and presentational styles that can be promoted to youngsters. These rules must be followed by advertisers, which may limit their marketing tactics and creative freedom.

Market Trends in Kids Digital Advertising Market

Growing Digital Platforms to Lead Global ...

As of the first quarter of 2022, the average advertising spending for mobile apps targeting children was over ***** times the amount spent on apps targeting grownups. In comparison, advertising spending in mobile apps not targeting children was indexed at **** across the Google Play Store and the Apple App Store.

Assume the car seat sales manager, who manages 400 stores, wants to be the company's top sales manager. The manager wonders how many sales other stores are currently making. However, the manager is only aware of his or her own sales data and has access to information about other stores. To determine the sales amount of other stores, the manager will create a sales predictive model, allowing the manager to estimate how much carseat sales are doing in other stores.

Dataset has 400 observations (each at a different store) and 11 variables:

|Variable| Description| |:-------------|:-------------| |sales | Unit sales in thousands| |comp_price | Price charged by competitor at each location| |income | Community income level in thousands of dollars| |advertising | Local ad budget at each location in thousands of dollars| |population | Regional pop in thousands| |price | Price for car seats at each site| |shelveLoc | Bad, Good or Medium indicates quality of shelving location| |age | Age level of the population| |education | Ed level at location| |urban | Factor levels 'Yes' or 'No' are used to indicate whether a store is in an urban or rural location.| |us | Factor levels 'Yes' or 'No' are used to indicate whether a store is in the United States or not.|

This data is part of data published on GitHub in this link

File Name: ifood_df.csv

The data is about result of 5 Marketing Campaigns done by food company, and how each customer interact with those campaigns, in addition to demographics data about customers such as: Income, age, education level, marital status, number of children and teenagers, and other data related to each customer

**I download it to Explore, Clean, and Transform it by Microsoft Excel, then Visualize and Analysis by Python ** First of all, in the Exploration Phase: Understand the column and the relationships between each column and others, Also Define the important questions which the way to make recommendations about the Marketing Campaign.

In the Cleaning Phase: Delete Columns “Z_CostContact” and “Z_Revenue” because it contains fixed number and not important for my questions. Delete column “Response” because it’s not used in my analysis and meaningless in addition to can’t find what’s that stands for! Then Check for missing data and I found that the day is Complete. After that check for duplicates and find out the every row is Unique. Also check for Accuracy and know that the data have correct and logical values. The only thing you should know that is the data not current, it's from more than 2000 customers from 2020.

Overall in Cleaning Process: The data is Accurate, Complete, Consistent, Relevant, Valid, and Unique. But need some Transformation.

In Transportation Phase: Add a column for “Index” to make a unique identifier for each customer. Aggregate all marital status in one column. Aggregate all education level in one column. Rearrange some columns like campaigns and Totals.

Fields Description:

Index: unique identifier for each customer. Income: the yearly income for each customer. Kidhome: number of small children in customer’s household. Teenhome: number of teenagers in customer’s household. Recency: number of days since last purchase. MntWines: Amount of wine purchased in last 2 years. MntFruits: Amount of fruit purchased in last 2 years. MntMeatProducts: Amount of meat purchased in last 2 years. MntFishProducts: Amount of fish purchased in last 2 years. MntSweetProducts: Amount of sweets purchased in last 2 years. MntRegularProds: Amount of Regular Products purchased in last 2 years. MntGoldProds: Amount of Special Products purchased in last 2 years. MntTotal: Total amount of everything purchased in last 2 years. NumDealsPurchases: number of purchases made with discount. NumWebPurchases: number of purchases made through company’s website. NumCatalogPurchases: number of purchases made using catalog. NumStorePurchases: number of purchases made directly in the store. NumWebVisitsMonth: number of visits to company’s website in the last month. AcceptedCmp1: 1 if customer accepts the offer in first campaign, 0 for otherwise. AcceptedCmp2: 1 if customer accepts the offer in second campaign, 0 for otherwise. AcceptedCmp3: 1 if customer accepts the offer in third campaign, 0 for otherwise. AcceptedCmp4: 1 if customer accepts the offer in fourth campaign, 0 for otherwise. AcceptedCmp5: 1 if customer accepts the offer in fifth campaign, 0 for otherwise. AcceptedCmpOverall: total number of marketing campaigns that customer accepted. Complain: whether the customer complained in last 2 years or not. Age: the customer’s age. Customer_Days: days since registration. marital_status: the customer’s status. education: the customer’s level of education.

Body Wash And Shower Gel Market size was valued at USD 46.70 Billion in 2023 and is anticipated to reach USD 70.88 Billion by 2031, growing at a CAGR of 5.47% from 2024 to 2031.Key Market Drivers:Components and Formulation: Natural, organic, and gentle components are becoming more and more popular among consumers when it comes to skincare products. Important factors are the lack of harsh chemicals like parabens and sulphates, as well as the inclusion of moisturizing substances like glycerin, shea butter, or essential oils.Fragrance: A key element influencing consumer preferences for shower gel and body wash is fragrance. Notes of flowers, fruits, citrus, or herbs are frequently found in popular smells. Sales may be boosted by the allure of a long-lasting scent or the advantages of aromatherapy.Skin Type and Concerns: Products designed to address particular skin kinds of issues, such as dry skin, sensitive skin, or acne-prone skin, have a big influence. Formulations that address these issues, such as hypoallergenic choices or items with additional moisturizers, are important motivators.Marketing and Advertising: Product benefits, USPs, and lifestyle connections can all be highlighted in well-thought-out marketing campaigns to pique consumer interest and boost sales. Product placements, influencer endorsements, and social media marketing can have a big impact.Price and Value: Sales can be boosted by pricing tactics that provide customers with a sense of value for their money, like bigger bottles or package discounts. Customers might also be prepared to spend more for premium components or a well-known brand.