The transition from modeling and measurement to tactical action within digital marketing is often riddled with challenges. The final numbers—those showing effectiveness, reach, and return—may prompt a daunting realization that past strategies need a revamp. Today we’ll navigate through the complexities of applying advanced attribution methods to overhaul marketing strategies, using detailed examples to illustrate these points. The Realities of Marketing Attribution Marketing attribution is an essential, though sometimes convoluted, aspect of any marketer's playbook. It's the process that connects the dots between the spend on marketing channels and the resulting business outcomes. In digital marketing, where the terrain shifts as rapidly as the online audience's attention, the right attribution model can mean the difference between a profitable campaign and a costly misstep. From Insights to Action For many direct-to-consumer (DTC) brands, Facebook prospecting is a cornerstone of their digital strategy. The process usually starts with a solid understanding of the attributed metrics provided by the platform—these are the self-attributed ROAS figures that Facebook provides based on its tracking. However, these numbers often tell an inflated story. By applying a multiplier that corrects for various biases and external factors, we arrive at a more accurate measure of Facebook's actual contribution to revenue. For instance, suppose a brand has been attributing $800,000 in revenue to Facebook prospecting. Upon applying an advanced attribution model that accounts for overlaps and cross-channel influence, the brand might find that Facebook's true contribution is only 70% of that amount. The 'haircut' this revenue takes would mean adjusting the figure down to $560,000. This new number—when divided by the same media spend—yields a more modest, yet more realistic ROAS. These adjusted figures force a strategic shift, prompting marketers to reassess the scale and efficiency of their Facebook spend. Non-brand search is another critical area, but one where brands often under-invest due to misleading data from traditional last-click attribution models. A test showing the true value of non-brand search can justify shifting more budget into this underestimated channel. For example, a Google platform might report $200,000 in revenue from non-brand search. By applying a larger multiplier based on incremental value—say, 80%—the adjusted revenue figure would be $160,000. When this new figure is set against the actual spend, the resulting ROAS could inform a more strategic deployment of search ad budgets. Emotions and Economics: Setting Marketing Goals The emotional attachment to certain channels can cloud judgment. When confronted with data that challenges long-held beliefs, marketers must navigate the emotional response to strategic change. In setting marketing goals, many teams rely on a variety of rationale—from intricate spreadsheets to goals inherited from past campaigns or even finance department mandates. The key is to establish goals that can adapt as new attribution data comes to light, ensuring strategies stay aligned with the most current and accurate picture of performance. Step by Step: The Road to Optimization Optimizing a digital marketing campaign can be distilled into three primary steps: Applying Results to Attribution: After adjusting platform reporting with multipliers, you obtain advanced attributed ROAS, which serves as a truer performance indicator. Comparison Against Goals: Align the new data with organizational goals to make informed decisions about where to scale back or invest more heavily. Budget Optimization: Allocate resources across the campaign portfolio, considering both large-scale and micro-optimizations within each platform. The granular details of optimizing within platforms like Facebook and Google Ads are where strategic decisions come to life. On Facebook, optimization may involve adjusting campaign settings to better align with advanced attribution findings. This could include setting caps on daily ad spend, tweaking CPM bids, or expanding target audience definitions to scale up prospecting efforts. For non-brand search, the optimization may start with refining keyword strategies within Google Ads but extend to enhancing the landing page experience to improve conversion rates. From adjusting CPC bids to optimizing ad formats and even iterating on website design, every tweak is aimed at squeezing out incremental performance gains. Organizing campaigns with granularity ensures that future optimizations are possible. By setting up separate campaigns for different audience segments, marketers can more accurately measure and compare performance, making it easier to allocate budgets and tailor strategies to each segment's unique behaviors and responses. The Advanced Attribution Advantage Advanced attribution isn't just about better measurement—it's a holistic approach to marketing strategy. It empowers marketers to make decisions grounded in data and devoid of the biases that often skew perception. Whether it's scaling a Facebook campaign or refining a keyword strategy for non-brand search, the aim is to employ a methodical, data-driven approach to every marketing decision. As we continue our evolving journey in the digital marketing domain, let's leverage advanced attribution not just as a tool for measurement, but as a strategic ally in our quest for marketing efficiency and effectiveness. With this approach, digital marketing stops being a gamble and becomes a calculated, continuously improving enterprise. Learn more through our Advanced Attribution Foundations short course. 

Understanding the landscape of customer acquisition costs (CAC) and incremental CAC (iCAC) in digital marketing isn't just about budget allocation—it's about strategic growth and market capture. Opportunity analysis can serve as the guiding light for informed decision-making in advertising spend. When a brand considers scaling its marketing efforts, opportunity analysis is the pivotal tool to navigate this expansion. By assessing the cost-effectiveness of various advertising platforms, opportunity analysis can reveal where your dollars can have a higher impact and which channels you can pull spend from. Profit or Growth: The Strategic Decision Informed by Opportunity Analysis Opportunity analysis isn’t just about finding the cheapest way to acquire customers—it is about aligning investment with business objectives. While some brands might prioritize demonstrating growth potential, others may choose profitability. Opportunity analysis serves as a critical component for this decision, offering a data-informed pathway to achieving the chosen end goal. Opportunity analysis is the strategic engine that drives smart investments and underpins successful scale-ups, underscoring the necessity of deep analysis, beyond the apparent data, to uncover the real story behind numbers. It is a story about where and when to place bets in the marketing game—a game that requires skill, strategy, and a bit of savvy speculation. In digital marketing, where every dollar counts, brands face the challenge of ensuring their budget allocation directly contributes to strategic growth and market penetration. Opportunity analysis serves as the vital tool to unlock this potential, guiding marketers to informed decisions that maximize return on investment. The Process of Conducting an Opportunity Analysis Opportunity analysis begins by taking your advanced attribution multiplier and segregating baseline sales—the portion of customer inflow that occurs without paid media influence—from media-influenced sales. Analyzing past advertising data will show that only a portion of your sales are influenced by paid efforts, leading to an adjusted perspective on the true cost of acquiring a new customer. A brand looking at their data through a base attribution lens the cost to acquire a new customer seemed straightforward: $57 per customer. However, with a deep dive into the data, including platform-specific nuances and multi-touch attribution (MTA) systems, the CPA swelled to $119. This inflation underlines how different attribution models can drastically alter CPA perception. CAC is the broader measure of total media spend over total new customers acquired, but iCAC fine-tunes this by considering only the new customers driven by media spend. Here, the baseline understanding is crucial, suggesting that a significant portion of business comes from non-paid media sources. In pursuit of growth, brands will face diminishing returns—a point where each additional dollar spent yields less than the previous one. Through opportunity analysis you can find the thresholds of efficient spend and the pitfalls of uncalibrated scaling. This predictive foresight allows brands to move forward with a refined strategy that would likely avoid the inefficiencies typically associated with ad spend saturation. Taking Action on Opportunity Analysis Opportunity analysis is not a static strategy; it's a vital, ongoing exercise that equips brands with the insight to make informed decisions and pivot as needed. Are you making the most of your marketing spend? Does your strategy consider the nuanced dance between growth and profitability? As you ponder these questions, remember: opportunity analysis is your guide. Now is the time to leverage this approach, transforming data into actionable growth plans.

Sensitivity Analysis in businesses today often encounter the challenge of measuring the efficacy of various advertising channels. The heart of this lies in attribution - the analytical science of assigning credit to the touchpoints a customer interacts with before converting. One of the most enlightening yet intricate parts of this puzzle is understanding how sensitive different channels are to various attribution methods. Today we delve into the world of Sensitivity Analysis in marketing attribution and offer insights into optimizing decision-making based on nuanced data interpretations. The Chameleon Nature of Channel Performance Metrics Take, for instance, a fashion brand analyzing its performance. The company sees a total of 74,000 orders, split almost evenly between new and returning customers, with a total media spend of roughly $2 million. Specifically, they funnel $1.3 million into Facebook for new customer acquisition. But here's where it gets tricky: you may see drastically different conversion and cost-per-acquisition (CPA) numbers depending on what attribution window you use! For example, at a one-day click window, Facebook may appear to have driven 17,000 new customers. However, with a 28-day click window, that number could inflate to 27,000. The CPA across these windows fluctuates significantly, from as low as $50 to over $230, indicating a dramatic variation in perceived efficiency. The fashion brand in question used to measure Facebook's performance with a one-day click and view, which showed Facebook as driving 17,000 customers at a CPA of $57 - closely aligned with their overall customer acquisition cost. However, an overlooked aspect was that not all reported conversions were from new customers, despite exclusion lists being used to separate out existing customers due to match issues and inaccuracies. Upon integrating data from Shopify, which employed UTM-based attribution, it was discovered that only 67% of Facebook's attributed orders were from new customers. This revelation recalibrated the new customer CPA from $57 to $85. Without even touching upon advanced attribution methodologies, this illustrated the sensitivity of the calculated performance metrics to the depth of data scrutiny. Advanced Attribution Multiplier: Reassessing Facebook’s Value The journey to refine the marketing attribution model further involves applying an advanced attribution multiplier, offering a more sophisticated perspective on a channel’s true incremental value. For example, when adjusting Facebook's numbers with a benchmark multiplier for mid-funnel initiatives such as lookalikes and broad audiences, the CPA climbed even higher to $120. This new figure stands in stark contrast to the initial $57 CPA, underscoring how significant the impact of attribution adjustments can be. Using this more rigorous model, Facebook's contribution to new customer acquisition drops to 29%, a more realistic portrayal of its true contribution to the business. This analytic progression showcases the variance in a channel’s performance based on the lens applied, emphasizing the need for marketers to adopt a multi-faceted approach to attribution. Cross-Channel Analysis: A Holistic View of Attribution While the example provided focused on Facebook, the principles of sensitivity analysis apply across all channels. By combining data sets from various platforms (such as Facebook, Shopify and other eCommerce platforms, or Google Analytics), and employing consistent methodology, businesses can assess the collective impact of their media efforts on both new and existing customer orders. In doing cross-channel analysis with this advanced approach, businesses can ascertain the unique and overall contribution of each channel to the company's success. This becomes especially crucial in environments where the attribution can often be skewed by customer behavior, platform biases, or simplistic analytic models that fail to capture the multifaceted nature of digital marketing. Sensitivity analysis is not just about number-crunching; it's a strategic beacon guiding marketers through the fog of complex digital interactions. It aids in deciphering the encrypted messages behind raw data, transforming numbers into narratives that inform smarter business decisions. As the attribution landscape continues to grow in complexity, the value of this analysis only deepens, becoming an essential compass for navigating the dynamic and often murky waters of marketing investment and performance. Businesses should regard sensitivity analysis as more than a retrospective audit of what has occurred; it's a forward-looking tool, a precursor to adaptive marketing intelligence. By continually questioning and calibrating the data at hand, companies can ensure their marketing strategies remain robust, responsive, and, most importantly, profitable in the long run.  Learn more about Sensitivity Analysis in our Advanced Attribution Foundations short course. 

Making informed decisions in the world of digital marketing is a complex task, requiring teams to juggle various factors to ensure that the strategies are not only effective but also efficient. In this two-part blog post, we will delve into the critical aspects of multi-touch attribution and how it impacts decision-making. We will also explore some tactics to illustrate these concepts, focusing on Facebook prospecting and non-brand search. Choosing the Right Tactics Effective multi-touch attribution necessitates careful consideration of the tactics used. For this discussion, we have selected Facebook prospecting and non-brand search, two common strategies employed by digital marketers. Facebook prospecting is frequently employed by direct-to-consumer (DTC) businesses due to its success in identifying and reaching their target audience. However, the metrics you see in the platform might not always reflect its actual performance. On the other hand, non-brand search often suffers from under-investment, primarily because last-touch metrics tend to undervalue its contribution. Examining these two tactics can shed light on the complexities and opportunities in multi-touch attribution. Applying, Comparing, and Optimizing in Multi-Touch attribution In our next post, we will break down the process of multi-touch attribution into three fundamental steps: applying, comparing, and optimizing. These three steps are essential to making informed decisions in the complex landscape of digital marketing. To apply multi-touch attribution effectively, we need to perform some straightforward media math and use the multipliers we derive from this. This allows us to calculate the new advanced attribution cost per acquisition (CPA) and return on ad spend (ROAS). And no worries, we will walk you through the process of doing this math. The comparison phase is crucial in making sense of the data generated through multi-touch attribution. This stage involves comparing the newly calculated advanced attribution CPA and ROAS against predefined goals. The thought process here is similar to analyzing last-touch metrics, albeit with more comprehensive insights. Once comparisons are made and the results are understood, the optimization phase begins. This is where decisions about budget allocation and tactic-specific adjustments come into play. We will explore both macro and micro optimization strategies: macro optimization involves reallocating budgets across platforms, while micro optimization focuses on fine-tuning tactics to enhance performance. Learning how to create efficiencies at both levels is key to unlocking greater opportunities in digital marketing. You don’t have to set out on the journey of multi-touch attribution alone. Many organizations rely on external partners, such as measurement solution providers and agencies, to guide them through this intricate landscape. These experts can offer recommendations on macro optimization decisions. However, understanding the finer details of optimization and being able to communicate effectively with your partners is essential to ensure that every aspect of your marketing strategy is optimized for success. By mastering the art of multi-touch attribution and optimizing strategies with precision, digital marketers can unlock the full potential of their campaigns. In the ever-evolving world of marketing, informed decisions are the cornerstone of success.

One of the buzzwords always echoing around the digital marketing industry is "multi-touch Attribution" or MTA. As marketing strategies and consumer behavior change, it's crucial to keep pace with changes in this area. In this post, we will explore the changing landscape of multi-touch Attribution and what you need to be aware of when utilizing it. MTA in the Marketing World MTA has become a staple in the marketing world, with many businesses exploring in-house versions of this model in addition to utilizing vendor offerings. The fundamental idea behind it is to assign credit for conversions to not one, but multiple touchpoints in the consumer journey. However, at further inspection, many teams discover that the effectiveness of multi-touch Attribution is no longer as robust as it once was. Data Scope Matters One of the critical aspects of multi-touch attribution is the scope of data it encompasses. In the past, you could collect comprehensive data from various platforms, including impressions, clicks, and conversions. This holistic view allowed for a clearer understanding of the entire consumer journey. However, the landscape has changed significantly. Now, the data scope is fragmented, and the ability to obtain a full consumer journey is becoming increasingly challenging. Each platform only provides insights into its own ecosystem. For example, Facebook's reporting focuses solely on Facebook impressions and clicks, and Google Analytics predominantly tracks on-site visits, often omitting critical information from other platforms like Snapchat or display advertising. The industry's journey towards a unified consumer experience has been disrupted. The Relative Approach In this new landscape, the best way to use multi-touch attribution is a more measured approach. Instead of seeking an absolute representation of the entire consumer journey, it's more effective to compare models and data sources. By analyzing relative comparisons, you can gain insights into how different marketing channels and touchpoints contribute to the customer journey. A practical example of the relative approach is comparing first-click attribution with last-click attribution. By examining the relative contributions of Facebook, Google Ads, and other channels in these different attribution models, you can uncover deeper insights consumer behavior. For instance, you might discover that many consumers initially interact with your brand through Facebook but only convert on a subsequent visit via search. In this way, you can gain a more nuanced understanding of the customer journey. Adapting to the Changing Landscape In today's landscape, the data you collect is often a sample of the overall consumer behavior. You're not observing the entire journey but rather a portion of it. Understanding this sampling approach will help you make more informed marketing decisions based on the data at your disposal. Conclusion Multi-touch attribution has shifted from an all-encompassing model to one that requires a more relative perspective. By comparing different attribution models and understanding the realities of data sampling, you can navigate the evolving marketing landscape more effectively. In a world where consumer behavior and marketing channels continue to change, adaptability and a willingness to learn and adjust are the keys to success. Learn more about advanced attribution techniques from our short courses. 

There’s no disputing it: businesses must harness the power of data-driven decision-making. One indispensable tool in a marketer’s toolkit is marketing mix modeling. In this post, we'll delve into what marketing mix modeling is, how it works, and how it empowers businesses to make more informed decisions. Understanding Marketing Mix Modeling At its core, marketing mix modeling is a regression model. While it can be as simple as a basic linear regression, more advanced models can be employed to correlate inputs to outputs. These models provide businesses with the ability to quantify the impact of both marketing and economic factors on their key performance indicators. Correlating Inputs to Outputs The primary goal of marketing mix modeling is to correlate these inputs with conversions, which can take the form of e-commerce sales, retail sales, app downloads, revenue, profit, or any other metrics that matter to a business. The model serves as a bridge between marketing activities and business outcomes, making it easier to evaluate the effectiveness of each component. Versatile Applications One of the key applications of marketing mix modeling is attribution analysis. Businesses can use the model to dissect the contribution of different factors to their sales. For example, it can reveal how much of the sales are attributable to TV advertising, Facebook campaigns, or specific seasonal trends. Any unexplained portion is often categorized as "base." Marketing mix modeling's versatility extends beyond just understanding media impact. Businesses can employ it for various purposes, such as analyzing competition, gauging the influence of seasonality, assessing economic conditions, or even examining how interest rates affect sales. This versatility makes it a powerful tool for data-driven decision-making. Model Constraints and Decision Support Once a marketing mix model is built, it's essential to remember that it has constraints. The model's capabilities are confined to the parameters of the inputs and outputs it was trained on. It is not a crystal ball, and asking it questions outside its bounds may lead to meaningless or misinterpreted results. Businesses should view the model as a decision support tool, which can provide valuable insights to shape strategies and guide marketing investments. Marketing mix modeling stands as a powerful tool in the modern marketing landscape. It helps businesses bridge the gap between marketing efforts and tangible outcomes, offering insights that can inform decision-making processes. By understanding the principles and nuances of this modeling technique, businesses can navigate the complex world of digital marketing with greater confidence and precision. Learn more about marketing mix modeling course at Msquared.

Creating a successful digital marketing campaign is a complex process that involves more than just running tests and analyzing results. It starts at the very beginning, with a strategic approach to setting up your campaigns. This thoughtful preparation can significantly impact the effectiveness of your digital marketing efforts. The Importance of Pre-Planning Before launching any campaign, consider the foundational elements of your strategy. These include your tactics, audience, objectives, and geography. Each of these factors plays a critical role in shaping your campaign's structure and potential success. When it comes to tactics, it's crucial to segregate different approaches into separate campaigns. For instance, retargeting and prospecting should never be mixed in the same campaign. These tactics yield different results and have distinct multiplier effects. Blending them makes it challenging to benchmark and analyze outcomes accurately. A recommended best practice is to exclude site visitors and existing customers from your prospecting tactics. This separation allows your prospecting to focus on acquiring new customers, leaving room for targeted campaigns aimed at site visitors and existing customers. Within each tactic, segmenting different audiences into their own campaigns is essential. This approach applies even to tactics that might seem similar, such as lookalike modeling and interest targeting. Separating these audiences allows for a clearer understanding of each group's performance and a more accurate application of multipliers. Facebook & Geographical Considerations On platforms like Facebook, having distinct objectives for each campaign is vital. For example, a lookalike conversion tactic should be tested differently from a lookalike traffic tactic, as they yield different multiplier results. Clear labeling and separation of these tactics are crucial for effective analysis. Geographically, it's advisable to run campaigns for different countries separately. While it might seem convenient to combine countries like the US and Canada, this approach complicates future geo-testing. If running multiple countries in a single account is necessary, ensure they are clearly and consistently labeled for ease of analysis. Consistency and Clarity in Campaign Management Consistency in campaign setup and labeling is crucial, especially when managing multiple campaigns across various geographies. Inconsistent labeling can lead to confusion and difficulty in identifying and analyzing specific campaigns. Consider the example of a client running campaigns in Australia. The campaigns were labeled inconsistently (Au, au S, Australia, international), making it difficult to sift through hundreds of campaigns to find specific ones. This inconsistency highlights the importance of a well-organized and clearly labeled campaign structure. In digital marketing, success often hinges on the clarity and strategic planning of your campaign setup. By paying close attention to the segregation of tactics, audience differentiation, clear objectives, and geographical considerations, marketers can create more effective and analyzable campaigns. Remember, the key to unlocking the potential of your digital marketing efforts lies in the details of your campaign's foundation.

In the ever-evolving world of digital marketing, businesses continuously seek efficient strategies to outperform their competition. One effective approach to achieve this involves a three-step process: Apply, Compare, and Optimize. This method offers a comprehensive way to enhance marketing performance using advanced attribution metrics. Step 1: Apply - Embracing Advanced attribution Metrics The first step in this transformative journey is to apply advanced metrics for more precise marketing analysis. Traditional last-touch metrics, while useful, often do not provide the complete picture of customer interactions. By employing advanced attribution Cost Per Acquisition (CPA) or Return on Ad Spend (ROAS), marketers can gain a more nuanced understanding of their campaigns' effectiveness. These metrics consider multiple touchpoints in a customer's journey, offering a more holistic view of their interaction with marketing tactics.Applying these advanced metrics requires a bit of media math. The idea is to take various multipliers and apply them to understand the advanced attribution CPA or ROAS. This mathematical approach allows for a deeper comprehension of how each marketing channel contributes to the overall success of the campaign. Step 2: Compare and Assess Against Goals Once these advanced metrics are in place, the next step is to compare these new results against set goals. This comparative analysis is crucial in determining the success of different tactics. If a campaign is outperforming the goals, it might be time to scale up the funding. Conversely, if a tactic is underperforming, reducing the budget or reevaluating the approach may be necessary.Comparing advanced Attribution results to goals enables marketers to make informed decisions about budget allocation. This process is similar to assessing last-touch metrics but provides a more comprehensive insight due to the advanced nature of the attribution models used. Step 3: Optimize - Fine-Tuning for Maximum Efficiency The final step is perhaps the most critical - optimization. This phase involves two key aspects: macro and micro optimization.Macro optimization focuses on the broader aspect of budget allocation across various platforms. It’s about understanding where to increase investment and where to cut back to maximize returns. This might involve reallocating budgets from underperforming channels to those delivering better results.Even if a tactic is meeting its goals, there’s always room for improvement. Micro optimization delves into the finer details of each tactic, identifying areas that can be further enhanced to boost performance. This could mean tweaking ad copy, adjusting target demographics, or experimenting with different content formats. The Role of External Guidance Companies often rely on external agencies or consultants for macro optimization recommendations, such as where to allocate or remove budget. However, the micro optimization often remains an area less explored by these external entities. Here, in-house teams can play a significant role. By understanding the nuances of micro optimization, they can work closely with agencies to ensure that every aspect of a campaign is fine-tuned for peak performance.The journey doesn't end with optimization. The digital marketing landscape is dynamic, and continuous learning and adaptation are key. Marketers should always be on the lookout for new tactics, technologies, and strategies to stay ahead in the game.By adopting a structured approach of applying, comparing, and optimizing marketing strategies, businesses can significantly enhance their digital marketing efforts. This methodology not only improves the efficiency of current campaigns but also opens up doors for future investment and growth. Embracing both macro and micro optimization ensures that every dollar spent is working towards achieving the best possible results. Ultimately, this approach is about being proactive, informed, and adaptable in the fast-paced world of digital marketing.

In digital marketing, data is king. And with multi-touch Attribution (MTA), marketers have a powerful tool at their disposal to make informed decisions and optimize their campaigns. In this three-step guide, we will explore the nuances of advanced Attribution metrics and how they can revolutionize your approach to digital marketing. Step 1: Implementing Advanced Attribution Metrics Creating a comprehensive dashboard is the first step in harnessing the potential of advanced attribution metrics. Your dashboard should be capable of consolidating data from various platforms, including Facebook, Google Ads, and any other platforms heavily represented in your marketing mix.  This dashboard will provide you with insights into your ad spend, total orders, and total revenue, allowing you a clear overview of your marketing performance. To take full advantage of advanced attribution metrics, you'll need to introduce some additional metrics to your dashboard. These new metrics will mirror the ones you're using for last-touch attribution, including advanced attributed orders, advanced attributed revenue, and advanced attributed ROAS (Return on Ad Spend) or CPA (Cost Per Acquisition). These metrics will paint a more complete picture of your campaign's effectiveness. As an example, consider a hypothetical Facebook prospecting campaign. In this scenario, you've achieved a self-reported ROAS of 6.2. However, this metric is based on Facebook's view of your campaign's performance, limited to its own ecosystem. It doesn't account for cross-channel interactions or customer behavior beyond Facebook. This is where advanced attribution comes into play. To calculate advanced attribution ROAS, you'll apply a multiplier. If your self-reported ROAS from Facebook is 6.2 and your multiplier is 72%, you'll get a new ROAS of 4.5. This revised metric offers a more accurate reflection of your campaign's actual performance across various touchpoints. Step 2: Comparing and Decision-Making with Advanced Attribution Metrics The next step is to compare your newly calculated advanced attribution metrics to your predefined goals. Setting these goals can be a complex process and may vary from brand to brand. However, an ROAS of $1.50 is generally considered the break-even point in many industries, while ROAS values between $2 and $3 are typically profitable. In our example, the brand had initially set a goal ROAS of 3.5 based on last-touch metrics. However, advanced attribution metrics led them to adjust their goals, providing a more accurate and ambitious target. This flexibility in goal-setting opens doors for more accurate budget allocation, ensuring that the brand invests where it truly matters. By comparing advanced attribution ROAS to the updated goal ROAS, marketers can make more informed decisions. If the results align with or surpass the goal, there may be an opportunity to scale up the campaign. If the results fall short, optimization or budget reallocation may be in order. For non-brand search campaigns, the introduction of advanced attribution can have a profound impact. While last-touch metrics might suggest budget reduction, advanced attribution might reveal untapped potential, encouraging brands to maintain or even expand their efforts. Step 3: Dive into the Nitty-Gritty of Optimization Once you've set the stage with your advanced attribution metrics and made data-informed decisions, it's time for the nitty-gritty of optimization. Micro and macro optimization both will come into play. Micro Optimization: Even if your campaign is performing close to your goal, there's always room for improvement. Micro optimization involves fine-tuning your tactics at a granular level to achieve even better results. Don't settle for meeting your goals; strive to surpass them and continue optimizing. Macro Optimization: The larger scale of macro optimization entails reallocating budgets between platforms and channels. Measurement solution providers and agencies can offer guidance here. They might suggest moving a certain amount from one channel to another or making strategic changes based on your advanced attribution metrics. Embracing advanced attribution metrics revolutionizes the way you approach digital marketing. It offers a more comprehensive view of your campaign's performance, allows for dynamic goal-setting, and enables you to make data-informed decisions. By diving deeper into optimization, you can unlock the full potential of your digital marketing efforts and stay ahead in the competitive landscape. Learn Next Step : When You Have Attribution multipliers: what’s next?