The Importance of Using Analytics in Advertising

Nowadays, businesses face the challenge of constantly refining their advertising campaigns to optimize performance. Given the complexity of the modern consumer’s journey, with its numerous touchpoints and channels, leveraging analytics in advertising plays a crucial role for businesses in achieving their desired outcomes. In 2022, Gartner reported that 53% of marketing decisions were driven by marketing analytics, and 75% of marketers anticipate that the role of analytics would become increasingly important over the next years.

However, a great number of businesses struggle with effectively analyzing and interpreting data to generate actionable insights and drive growth. In this article, our expert, Darya Kislova, is explaining how advertising analytics can overcome these challenges and systematically enhance ROAS/ROI on your current level of analytics complexity (Basic, Intermediate, or Advanced). Then, you will learn how to move on to the next level(s). Finally, we will discuss the strategy for ongoing optimization. But first, let’s delve into the basics of advertising analytics and the benefits you will get.

Table of Contents:

1. What is Advertising Analytics?
2. What are the Benefits of Advertising Analytics?
3. The Three Levels of Optimization
4. Basic Level: ROAS Optimization
5. Intermediate Level: Net ROAS Expansion
6. Advanced Level: Incremental ROAS (iROAS) Assessment
7. Strategy For Ongoing Optimization
8. Conclusion
9. Using Analytics in Advertising FAQs
10. Choose VIDEN to Create and Implement Actionable Advertising

What is Advertising Analytics?

Advertising analytics is the process of measuring, analyzing, and optimizing ad campaign performance by leveraging data generated from various sources, such as websites, social channels, software applications, and mobile devices. Data analytics in advertising allows you to improve attribution, campaign optimization, and resource allocation.

What are the Benefits of Advertising Analytics?

As you can see, there are many advantages you as a business can explore. Let’s discover some benefits of using advertising analytics:

1. You can get a comprehensive view of the customer journey

You can enhance attribution by tracking the customer journey and pinpointing every touchpoint a customer interacts with on their path to purchase. With a unified perspective on all customer interactions with your company, you gain deeper insights into their needs and preferences and make more informed decisions when planning future campaigns.

2. You can generate insights for targeting the ideal audience

Analytics enables you to identify common characteristics among your best customers, allowing you to target similar audiences. So, focus on segments based on acquisition cost, lifetime value, and other crucial metrics.

3. You can enhance personalization

Data analytics insights allow you to create personalized customer journeys tailored to each segment. You can confidently deliver the right message through the right channel at the optimal time to maximize campaign performance.

4. You can optimize campaign performance

Campaign performance optimization is a multifaceted process. You can optimize campaign performance by measuring and testing various elements, for example messaging, ad layout, and calls to action.

5. You can allocate resources

Determine which channels to invest in more and which to scale back. You can optimize resource allocation, including ad spend.

6. You can boost forecast accuracy

Forecasting is challenging for marketing teams due to numerous variables affecting campaign performance. Advertising analytics allow you to measure past performance and make more accurate future predictions. Scenario modeling helps you identify likely outcomes based on various campaign impacts, improving your ability to forecast lead volume and conversion rates accurately.

These benefits can be fully realized through understanding and implementing the 3 levels of optimization. Let’s discover them.

The Three Levels of Optimization

Effective advertising depends on transforming a plethora of data into actionable insights. This process is critical to developing strategies to maximize financial returns.

Each level of analytics complexity is built on the previous one, requiring businesses to build a solid foundation of basic practices before moving on to more advanced methods. So, let’s dive deeper into a basic level.

Basic Level: ROAS Optimization

This level is essential for all businesses looking to maximize their marketing performance. Without a solid understanding of fundamental analytics, moving to higher levels is ineffective and fails to deliver the desired returns.

Let’s look at the ROAS formula. ROAS measures the effectiveness of advertising spend in generating revenue. ROAS is the function of:

Metrics and definitions to be tracked on this level

• Average Order Value (AOV): The average value per order (cart/basket size)
• Conversion Rate (CVR): The percentage of visitors who complete a desired action, such as making a purchase.
• Click-Through Rate (CTR): The ratio of users viewing the ad who click on it
• Cost Per Thousand Impressions (CPM): The cost for 1,000 advertisement impressions, the reflection of competition
• Cost Per Click (CPC): The cost paid for a click on an ad

Let’s take an example. An eCommerce store has an actual ROAS of 2.5X, with:

CPM=$10

CTR=1%

AOV=$50

CVR=5%

Now, let’s address the question that concerns every business owner.

How can a business improve the ROAS, for example by 20% (i.e. to 3X)?

Assuming the competition remains the same (i.e., no changes in CPM), a 20% boost should come from improvements in CTR, CVR, or AOV.

V1: If the business increases CTR by 7% (to 1.07%), AOV by 5% (to $52.5), and CVR by 7% (to 5.35%), we will get the following:

ROAS = ($52.5*5.35%*1.07%*1000)/$10=3.0

V2: If the business increases CTR by 5% (to 1.05%), AOV by 10% (to $55), and CVR by 4% (to 5.2%), we will have the following:

ROAS = ($55*5.2%*1.05%*1000)/$10=3.0

Key analytical points

To improve ROAS, several analytics practices in different aspects of ecommerce and marketing can be employed, focusing on influencing key components (such as CTR, AOV or/and CVR):

• Product Analytics
• Conversion Funnel Analytics or CRO
• Ads Analytics

Let’s examine these practices and explore how relevant analytics techniques can significantly improve the effectiveness of different advertising strategies.

Product Analytics uncovers associations between sets of items that customers frequently purchase together. AOV and CVR (product view to purchase) are analyzed as primary KPIs.

Some areas/ideas to approach it:

• Product affinity analysis (to cross-sell, upsell, bundle best selling products together): 7% improvement in AOV, as a result 7% better ROAS.

• Price & sales/offerings elasticity analysis (finding/testing optimal price point for products): 15% improvement in AOV, leading to an 8% decrease in CVR, leading to 6% better ROAS.

• Inventory management optimization.
• Product placement optimization.
• Market basket analysis, etc.

Conversion Funnel Analytics or CRO (conversion rate optimization) allows to analyze each step of the customer journey to identify drop-off points and barriers that impact conversion rates, allowing for targeted improvements. CVR is an analyzed primary KPI. 

Some areas/ideas to approach it:

• Funnel drop-off analysis.
• A/B testing.
• User experience (UX) audit: the recommendations employed improved CVR by 7%, leading to a direct 7% increase in ROAS.

• Content effectiveness analysis, etc.

Ads Analytics can measure the effectiveness of advertising campaigns by evaluating outcomes per click or view, helping understand which ads drive the best results at the lowest cost. CTR is an analyzed primary KPI.

Some areas/ideas to approach it:

• Creative type testing (videos, images, carousels, product ads, etc.).
• Creative messaging: hooks, ad description, etc.
• Creative placement (where ads are shown).
• Industry trends analysis, etc.

By evaluating the important metrics, optimal creatives were identified. CTR increased by 4%, leading to a 4% improvement in ROAS after implementing changes.

Attaining a fundamental level of ROAS optimization is crucial for businesses aiming to enhance their marketing performance. By incorporating analytics into a product, conversion funnel, and ads strategies, businesses can get a reliable estimate of the immediate return on their advertising efforts and build the foundation for more advanced strategies to improve profitability by moving toward a more comprehensive approach to marketing efforts. Once you complete the basic level, you can advance to the next one.

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Intermediate Level: Net ROAS Expansion

Once the basic level—ROAS optimization—is covered, businesses can progress to the intermediate level, where the focus shifts to maximizing net profitability. At this stage, Net ROAS is introduced, which estimates the real effectiveness of advertising expenditures, considering not just revenue but also other costs such as operational expenses, cost of goods sold, content production, taxes, etc.

At the intermediate level, it is important to understand that ROAS targets vary significantly depending on product margins, and estimating Net ROAS provides a clearer picture of marketing effectiveness.

Let’s consider the example that illustrates how two products with the same Net ROAS can have significantly different ROAS values due to differences in profit margins.

Product 1: High-Value Product

• Product Price: $2000
• Units Sold: 100
• Total Revenue: $200,000
• Cost of Goods Sold (COGS) per unit: $1250
• Total COGS: $125,000
• Other costs: $15,000
• Taxes: $30,000
• Ad Spend: $10,000

Total Costs: $180,000

Net Profit: $200,000 – $180,000 = $20,000

Net ROAS=Net Profit/Ad Spend=20,000/10,000=2.0X

ROAS=Revenue/Ad Spend=200,000/10,000=20.0X

Product 2: Low-Value Product

• Product Price: $40
• Units Sold: 2000
• Total Revenue: $80,000
• Cost of Goods Sold (COGS) per unit: $5
• Total COGS: $10,000
• Other Costs: $24,000
• Taxes: $16,000
• Ad Spend: $10,000

Total Costs: $60,000

Net Profit: $80,000 – $60,000 = $20,000

Net ROAS=Net Profit/Ad Spend=20,000/10,000=2.0X

ROAS=Revenue/Ad Spend=80,000/10,000=8.0X

Using standard ROAS can lead to misleading conclusions for products with different margins. Hence, focusing on net ROAS offers a more accurate and financially sound approach to evaluating and optimizing advertising spend.

Steps to incorporate Net ROAS into analytics:

1. Finding products with the highest and most profitable margins
2. Clustering products (grouping) with similar margins
3. Defining optimal ROAS to optimize against based on Net ROAS
4. Determine optimal scale

On an intermediate level businesses should consider a broader range of strategies beyond the basic examination of revenue versus ad spend.

Some areas/ideas to approach it:

• Incorporating Customer Lifetime Value (CLV): Adjust advertising spends based on the projected long-term revenue from customers, allowing for more targeted and cost-effective marketing strategies.
• Break-even Point Analysis: Calculate the break-even point for each product or campaign to understand how much needs to be spent on advertising to start generating a profit. This helps in setting more accurate budget limits and ROAS targets.
• Sentiment Analysis: Use sentiment analysis to tailor marketing content more effectively, thereby reducing production costs and improving ad effectiveness by resonating better with the target audience.

Net ROAS ensures that marketing strategies are not only effectively generating revenue but also contributing positively to the overall profitability of the business. Examining this metric allows companies to align their marketing efforts with financial goals more closely, so it’s important to research and implement strategies that maximize Net ROAS. After completing the intermediate level, you can move to the final one.

Advanced Level: Incremental ROAS (iROAS) Assessment

Following the exploration of ROAS optimization and Net ROAS in previous discussions, the focus now shifts towards a more nuanced metric in the advanced level of marketing analytics—Incremental ROAS (iROAS). This progression is essential as businesses seek to understand not just the general effectiveness of their advertising spend, but the specific additional value generated by particular marketing efforts over a defined baseline.

• Incremental Revenue: The additional revenue generated directly by marketing activities, isolated from the baseline performance.
• Incremental Advertising Spend: The additional budget allocated to specific marketing campaigns intended to drive incremental sales.

To better illustrate the concept of Incremental ROAS (iROAS), let’s consider a hypothetical scenario: an eCommerce company launches a new digital marketing campaign and gets the following results:

• Total Advertising Spend: $100,000
• Total Revenue Generated: $300,000
• ROAS: $300,000 / $100,000 = 3.0

In the example provided, ROAS of 3.0 suggests that the company generates three dollars for every dollar spent, but it doesn’t fully account for all variables influencing sales and potentially overstates the impact of the new advertising campaign due to not isolating its unique contribution.

To understand the value added by this specific advertisement, we divide the audience into two groups: a control group that was not exposed to the campaign and a test group that was:

• Revenue from Control Group (no ads): $200,000
• Revenue from Test Group (exposed to ads): $300,000

The incremental revenue attributed directly to the campaign is $100,000 (the difference between the test group and control group revenues).

Incremental Advertising Spend: $100,000 (the additional spend for this specific campaign)

iROAS = $100,000 / $100,000 = 1.0

This iROAS of 1.0 reveals that the campaign effectively only generated a dollar for every dollar spent when considering the incremental impact.

Incrementality provides a clearer picture of how the additional spend directly contributes to revenue growth, supporting targeted decision-making in marketing strategy.

Practical Steps to Define iROAS:

1. Implementing comprehensive data collection across all user touchpoints. I
2. Designing experiments with clear objectives and hypotheses.
3. Segmenting your data to analyze the differential impact of campaigns across various customer groups. This can help tailor strategies to maximize iROAS in specific segments.
4. Regulary updating your models and hypotheses regularly based on ongoing results and changing market conditions.

Some areas/ideas to approach it:

• Media Mix Modeling (MMM): A statistical analysis technique that quantifies the impact of various marketing tactics on sales and then forecasts the impact of future sets of tactics. MMM helps allocate marketing budgets by determining the effectiveness of each marketing channel at scale.
• Conversion Lift Studies: Utilize controlled experiments to directly measure the increase in conversion attributable to specific marketing activities. These studies help isolate the impact of a campaign by comparing the behavior of a group exposed to the campaign against a similar group that was not exposed.
• Causal Attribution: Advanced modeling techniques that go beyond traditional attribution models to understand the cause-and-effect relationships between marketing actions and consumer behavior. This approach helps marketers see which specific actions are driving outcomes.

By strategically applying these techniques, marketers can more accurately measure and optimize their marketing efforts for incremental gains, ensuring that each dollar spent contributes to measurable and substantial business growth.

Now, let’s delve into the iROAS of various marketing channels to see how it differs from Net ROAS and basic ROAS.

On the advanced level, the focus is on understanding the specific added value of marketing efforts, which is critical for businesses seeking to accurately optimize their advertising spend. This approach indicates the need for accurate measurement to analyze the direct contribution of specific campaigns to ensure that every dollar is adding real value to business growth.

Strategy for Ongoing Optimization

Implementing a structured process of ongoing analysis is crucial to ensuring that marketing strategies remain dynamic and responsive to market changes. This is the key to sustainable marketing success. The strategy involves the following:

• ROAS’s Daily Health Checks
• Weekly Reviews
• Monthly/Quarterly Analysis

Let’s explore these strategies more precisely.

Daily Health Checks of ROAS help track the immediate effectiveness of ad spend, allowing for rapid adjustments to optimize advertising expenditures. Ершы should be a routine part of operations, where systems are monitored for anomalies, bugs, and immediate performance issues. This proactive observation allows for swift responses to technical disruptions, maintaining seamless operations and ensuring data integrity.

Weekly Reviews should include an analysis of Net ROAS to evaluate both the return and the cost efficiency of advertising strategies over the past week. This deeper dive helps to identify performance trends and tactical opportunities for refinement. Regular revaluation of these metrics helps to stay aligned with evolving market dynamics, ensuring that strategies are adjusted to continue driving desired outcomes.

Monthly/Quarterly Analysis should expand to include iROAS, which measures the additional return generated by specific marketing initiatives beyond regular operations. This is more comprehensive, serving as a strategic session that uses the latest data to inform and shape future plans. This analysis is crucial for understanding the broader implications of current tactics and adjusting long-term strategies accordingly to ensure that marketing efforts are well-aligned with overarching business goals, optimizing resource allocation, and maximizing overall profitability.

This continuous cycle of monitoring, reviewing, analyzing, and adapting allows marketing analytics to meet industry standards and also to anticipate and effectively respond to new challenges and opportunities. This comprehensive approach enables organizations to persistently refine their efforts, leading to sustained marketing excellence and a competitive edge in the marketplace.

Using Analytics in Advertising FAQs

How to analyze advertisements?

Begin with ROAS optimization to maximize advertising spend efficiency and enhance immediate returns. Next, move on to ROI expansion to evaluate the additional value generated by specific marketing efforts beyond the established baseline, emphasizing their direct impact on sales and brand perception. Finally, conduct an incremental ROI assessment to determine the extra value created by these marketing initiatives, focusing on their direct influence on sales and brand perception.

What are the key metrics to track in ad analytics?

On the basic level, you can analyze Average Order Value (AOV), Conversion Rate (CVR), Click-Through Rate (CTR), Cost Per Thousand Impressions (CPM), and Cost Per Click (CPC). The intermediate level includes metrics such as Customer Lifetime Value (CLV), Customer Equity, and Net Promoter Score (NPS). On the advanced level, you can analyze Incremental ROI (iROI), Incremental Sales (iSales), Incremental Profit (iProfit), and Brand Lift.

How can I use data analytics in advertising for social media marketing?

Social media analytics gathers and examines audience data from various social networks, providing valuable insights to enhance an organization’s strategic business decisions. By analyzing patterns of social media post popularity, you can measure the effectiveness of social media campaigns, identify trends, understand customer sentiment, and estimate future trends.

Conclusion

Leveraging analytics in advertising to optimize marketing results is an indispensable strategy in today’s digital landscape. By employing a structured approach that progresses through basic, intermediate, and advanced levels of analytical sophistication, businesses can enhance their understanding of ROAS. Starting with basic tactics to optimize ROAS, evolving through intermediate strategies to refine net profitability, and advancing to comprehensive analyses that evaluate incremental gains, companies can transform data into actionable insights. Through this dynamic cycle of analysis and adjustment, organizations can achieve a deeper synergy between their marketing initiatives and overall business objectives, driving sustained growth and success.

If enhancing your marketing strategies is a priority, consider VIDEN’s expert services. Contact usto maximize your marketing effectiveness.