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How High Performing Marketing Teams Are Embracing Technology for Success

In today’s increasingly digital and data-driven world, marketing teams are turning to technology to navigate and thrive. With the creation of advanced analytics platforms, these teams are witnessing the tremendous benefits such tools bring to building a successful marketing plan. However, under-equipped teams face new challenges in the absence of proper marketing measurement tools.

To gain a deeper understanding of how top-performing marketing teams leverage advanced technology, Keen recently surveyed full-time marketers at mid-market or enterprise companies. In this blog, we will share the findings of the 600+ respondents about how these high-performing teams are leveraging technology for measurement and forecasting. We will also share how it is shaping the skills necessary for success, and the impact it is having on the revenue generated by their marketing efforts.

Advanced analytics and campaign effectiveness

According to our survey, 86% of marketers who use technology for these purposes turn to analytics platforms, which have proven to be increasingly valuable. Here are some key findings:

  1. Enhanced Campaign Effectiveness: A staggering 91% of marketers reported that integrating advanced analytics platforms into their campaigns contributed to their overall effectiveness in the past year. By leveraging data-driven insights, marketing teams are able to optimize their strategies and make data-backed decisions.
  2. Facilitating Personalization: With the decline of traditional cookies, marketers are finding personalized targeting a challenge. However, 81% of marketers believe that analytics platforms are essential for facilitating personalized experiences. These tools enable teams to understand customer behavior, preferences, and demographics, thereby creating tailored campaigns that resonate with their target audience.

Yet, challenges arise when marketing performance measurement tools are not properly implemented. Teams lacking these tools face data limitations in various areas:

  1. Interactions Between Marketing Channels: 66% of teams without suitable measurement tools struggle to track and understand interactions between different marketing channels. This opacity hinders the ability to optimize marketing strategies for maximum impact.
  2. Budget Management: 45% of under-equipped teams lack sufficient data for effective budget management. This creates inefficiencies, as marketing spend is not accurately allocated to the most lucrative channels or campaigns.
  3. Precise Allocation of Spend: Similarly, 41% of marketers lack the ability to precisely allocate their marketing spend due to insufficient measurement tools. This prevents them from optimizing their budgets and maximizing returns on investment.

Challenges in marketing measurement implementation

It’s worth noting that senior leadership (37% more likely than average) recognizes the importance of proper marketing measurement tools for accurate budget management and spend allocation.

Unfortunately, implementing these measurement tools is not without its challenges. 80% of marketers surveyed found integrating these tools into their overall strategy to be moderately or highly challenging. This complexity may arise from integration issues with existing systems, skill gaps, or resistance to change.

High-performing marketing teams are embracing technology and harnessing the power of analytics platforms to optimize their campaigns. These tools provide the necessary insights for effective measurement, personalization, and budget management. However, under-equipped teams face challenges in leveraging these benefits, resulting in limited data on marketing channel interactions, budget management, and precise spend allocation. Overcoming these challenges and implementing measurement tools effectively is crucial for marketing teams to excel in today’s competitive landscape.

Download the “Mastering Measurement: The CMO’s Guide to Building High-Performing Marketing Teams in 2024″ eBook of complete survey findings here.

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Challenger brand drives revenue and profit – with less investment

Challenger brand drives revenue and profit - with less investment

By maximizing the power of the Keen Platform, this challenger brand used the platform's capabilities to pivot their strategy and find the right mix that would achieve their new growth goals in the most profitable way possible.

 

Read the full case study to see how this team was able to drive revenue and profit with less investment.

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The Role of AI in Building High Performance Marketing Teams

Assembling high-performing marketing teams is a dynamic and complicated process. The skills, experience, and role-specific expectations marketing leaders search for are constantly evolving, especially as we become more reliant on digital tools. With the marketing landscape becoming increasingly crowded with new channels, the pressure on marketing teams is higher than ever. Keen wanted to gain a better understanding of the challenges faced by these teams and how technology is being harnessed to overcome them.

Keen recently surveyed full-time marketers at mid-market or enterprise companies. In this blog, we will share the findings of the 600+ respondents about how they feel artificial intelligence (AI) is impacting the performance of their marketing team.

In 2023, AI made significant waves and its integration into various industries is set to expand in the coming years. The field of marketing is no exception to this trend. Currently, 41% of marketing teams that utilize tools for measurement or forecasting are already utilizing AI-driven technology. Furthermore, two out of three marketers have stated that their companies are directing investments towards AI and machine learning tools specifically for marketing performance measurement in 2024.

AI-Driven Technologies: A Game Changer in Revenue Growth

One of the most tangible advantages of AI in marketing is its impact on revenue. Half of the respondents who reported that their company invests in AI tools claimed to have witnessed increased revenue as a direct result. Interestingly, senior leadership individuals were 42% more likely than average to express this sentiment. On average, the implementation of AI-powered tools has led to a revenue lift of around 24%.

However, AI’s significance extends beyond immediate returns on investment; it empowers marketers to confidently navigate the future. Marketers who currently invest in AI have reported numerous favorable outcomes, including a greater ability to make better future marketing decisions (57%) and improved forecasting (49%). Once again, senior leadership individuals were 33% more likely to acknowledge these benefits.

While AI is not intended to replace human workers, marketers must adapt and embrace this technology to remain competitive. An overwhelming 86% of respondents agreed that adaptability to emerging technologies is a core competency for marketing team members. Moreover, providing teams with the latest and most advanced technology is vital for employee retention. Roughly 60% of teams currently invest in AI tools to support marketing measurement, and 47% of those who do not expressed a preference to work for a company that does.

The Risks of Overlooking AI in Marketing Strategies

Companies that neglect AI investments risk falling behind their competitors and placing unnecessary strain on their marketing teams. Marketers lacking AI tools for marketing measurement argue that such tools would grant them more time to focus on revenue-generating activities (65%), make their jobs easier (65%), and enhance overall campaign performance (60%). It is evident that AI is becoming a crucial element in the marketing industry, with organizations and marketers recognizing its potential and embracing its capabilities for future success.

Download the “Mastering Measurement: The CMO’s Guide to Building High-Performing Marketing Teams in 2024″ eBook of complete survey findings here.

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Introduction to Scenario Based Marketing Planning

In today’s rapidly changing market environment, the ability to anticipate and effectively respond to potential future scenarios is more crucial than ever before. Scenario-based marketing planning emerges as a strategic approach designed to help brands navigate through uncertainties with confidence. This methodology involves identifying and analyzing possible future events or conditions—ranging from economic shifts, technological advancements, competitive movements, to consumer behavior changes—and developing strategies to address each potential scenario.

By employing scenario-based marketing planning, brands are not only able to mitigate risks but also seize opportunities that may arise from future market dynamics. This approach requires a thorough understanding of the current market landscape, predictive analysis, and creative thinking to envisage various future states. Scenario planning equips marketers with a proactive blueprint, enabling them to adapt quickly and maintain a competitive edge in ever-evolving markets.

Keen's Approach to Scenario-Based Marketing Planning

At Keen, we recognize the vital role of scenario planning in equipping businesses to thrive amid market uncertainties. Our approach to scenario-based marketing planning is designed to empower brands with actionable insights and strategic flexibility, positioning them for success in any future market environment.

Building a Baseline for Effective Scenario Planning

The foundation of effective scenario-based marketing planning lies in building a solid baseline, a comprehensive understanding of the brand’s past and current performance and strategy. The Keen Platform makes this process seamless through our comprehensive lists of integrations and easy file management system. This process is outlined below and in our bayesian regression blog. 

Scenario Planning in Action: Real-World Applications

With Keen’s scenario planning features, Twinings was able to: 

– Predict the financial impact of each of its channels—digital, online and trade—to compare and make decisions. This unified measurement sets a new standard for marketing decision support. 

– Optimize in real time to model a prescriptive, weekly plan to drive incremental revenue without spending past the point of diminishing returns when timing was optimized.

– Identify key investment opportunities in under used tactics.

Read the full Twinings case study.

Future Forecasting and Competitive Analysis and Crisis Management

Scenario planning is more than prediction; done well it is an exercise in anticipation with an emphasis on preparing for the unpredictable. By incorporating future forecasting and competitive analysis into scenario planning, businesses can evaluate various market conditions, technological advancements, consumer behavior changes, and potential moves by competitors. 

For instance, the Keen Platform can help your team simulate the likely performance of a competitor and consequently you can make strategic decisions for the health of your brand. 

In addition to a dynamic market, today’s marketer has to anticipate crises that can emerge unexpectedly, driven by factors such as technological failures, natural disasters, or social and economic disruptions. This preemptive planning ensures that businesses can mitigate the impact of crises, maintaining brand integrity and customer trust during challenging times. This was especially relevant during Covid.  Keen helped marketing teams navigate supply chain and consumer behavior disruptions and our scenario planning capabilities allowed the teams to pivot their marketing strategies to adjust to these external factors. 

For example, one global retailer might use scenario planning to prepare for supply chain disruptions caused by geopolitical tensions or natural disasters. By identifying alternative suppliers and logistics routes in advance, the company can ensure continuity of operations and minimize any negative impact on customer satisfaction and financial performance.

The Keen Platform allows marketing teams to manage risks almost as dynamically as hedge funds.

Implementing Scenario Planning in Marketing Strategy

Integrating scenario planning into a marketing strategy equips brands with the foresight and flexibility to stay ahead in a turbulent market environment. By anticipating future developments and preparing for various outcomes, businesses can seize opportunities and mitigate risks more effectively.

Steps to incorporate scenario planning

To successfully integrate scenario planning into marketing strategy, businesses should follow these steps:

Steps to integrate scenario planning into marketing strategy
Identify key drivers of changeDetermine the critical factors that could influence the business environment, including technological trends, consumer behavior shifts, regulatory changes, and competitive dynamics.
Develop scenariosCreate a range of plausible scenarios based on the identified drivers, considering both optimistic and pessimistic outcomes.
Analyze implicationsEvaluate the potential impact of each scenario on the organization's marketing strategy, identifying opportunities and threats.
Formulate strategiesDevelop flexible and adaptable marketing strategies that can be quickly deployed based on the unfolding scenario.
Monitor and reviewContinuously monitor the business environment for signs that a particular scenario is becoming more likely and adjust the marketing strategy accordingly.

Conclusion: The Strategic Advantage of Scenario-Based Planning in Marketing

Scenario-based planning represents a strategic cornerstone for enterprises seeking a proactive stance in their marketing strategies. This approach allows organizations to navigate the complexities of market dynamics with a forward-thinking mindset, equipping them with the agility to adapt to unforeseen circumstances rapidly. By incorporating scenario planning into their marketing strategy, companies are not only preparing for potential challenges but are also positioning themselves to seize emerging opportunities before their competitors do.

The benefits of scenario planning using the Keen Platform are:

  • Enhanced decision-making agility in a dynamic and interactive go-forward framework
  • Rapid competitor analysis and marketing measurement
  • Risk management, hedge your strategy among likely scenarios

Want to see our scenario planning functionality in action?  Take a tour of the platform today!

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Dental product brand doubles down on TV spend and see returns of $8M in marketing-driven profit

Dental product brand doubles down on TV spend and see returns of $8M in marketing-driven profit

By leveraging the Keen Platform, our dental product client was able to test scenarios for their traditional TV marketing plan.  They scenario they landed on indicated investing an additional $1.8M could deliver millions in additional topline growth and profitability, compared to their status-quo plan.

Read the full case study to see how this team accepted the risk and outperformed the projected ROI and made TV the single largest driver of brand growth in that year.

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AdQuick and Keen Partner to Plan, Optimize, Forecast and Measure OOH Investments

Empowering Predictive Media Planning: AdQuick’s New Partnership with Keen Decision Systems Unlocks Real Time OOH Measurement and Optimization

Keen Decision Systems, a real-time marketing mix optimization SaaS platform powered by AI, announces an exclusive partnership with AdQuick, the premier platform for Out-of-Home (OOH) advertising that simplifies the planning, buying, and measurement of all types of outdoor advertising. This strategic alliance enables advertisers to effectively bridge the gap between Return on Ad Spend (ROAS) and Revenue by assessing both the immediate and long-term impacts of OOH advertising on revenue and profit ROI.

Through this partnership, AdQuick will power OOH measurement within the Keen Platform, providing Keen users with immediate access to OOH spend and impression delivery data. This integration will enable robust MMM measurement, omni-channel optimization, and forward-looking scenario planning.

“OOH advertising offers an unparalleled combination of dwell time, location-based targeting, and impactful formats. But, it has been undervalued, often relegated to ‘awareness’ rather than recognized for its full-funnel potential,” states Jesse Math, VP, Strategic Partnerships at Keen. “Our partnership addresses this gap head-on, positioning OOH as a key player in marketing strategies by quantifying its true influence on revenue, profit, and ROI. With Keen, advertisers are now equipped to forecast and maximize OOH’s value through detailed scenario planning.”

“We’re beyond grateful to Keen for partnering with us to solve today’s ubiquitous problem of advertisers simply not knowing how much financial return their OOH investments are generating.  All of OOH, including static and digital, can now be effectively measured in Keen, and this is a gamechanger for Keen’s clients because the possibilities now uniquely exist for seeing OOH’s impact on growing financials, as well as quantifying the impacts of optimizations on capturing more value from OOH (i.e. what is the value of using 1st and 3rd party data in OOH placement selections?).  It’s our hope that all of Keen’s clients take advantage of this opportunity, break away from the status quo and capture the untapped potential that OOH really offers.” – Jason Kunkel-de Cesero, Vice President, Demand & Analytics Partnerships 

“The rapid advancements in technology are now lining up with and extending our efforts for over a decade where we focused on methods and practices that enable us to bring together the 110,000 static and digital displays of our 300 media companies across the country,” said Chris Cowlbeck, IBO USA CVO. “I’ve been told repeatedly for several years that the process needed to be easier and that we needed to help the buy side prove the value of OOH, and now the aligning of the stars with like-minded players will enable us to reach our goals and enable brands to achieve theirs. By focusing on robust data and metrics processes, the gaps can now begin to close to bring the results we all desire and have spent years pursuing.  IBO USA members will grow our interest and commitment of easing buying and improving focus to strengthen attention of the industry and the trust in campaign metrics. The Keen + AdQuick partnership adds dimensions to locations that we haven’t been able to have previously and really will enhance the understanding of our static and digital inventory.”  

A New Era of OOH Advertising Confidence

The partnership between Keen and AdQuick offers novel capabilities to advertisers for assessing & optimizing OOH advertising. Keen’s patent-pending Marketing Elasticity Engine, equipped with channel-specific ROI “priors” tailored to each advertiser’s category and P&L size, provides predictive analytics that enable advertisers, including those new to OOH, to accurately predict its impact on business outcomes, taking into account the halo interactions with existing digital channels.

An Interoperable Measurement Ecosystem

Keen fills the “so what?” gap left by most marketing measurement, embodying a financial-based decisioning platform that respects the ‘source of truth’ within marketing organizations. Advertisers are invited to integrate results from diverse methodologies, including match market tests and incrementality, into the Keen Platform to evaluate alongside Keen’s measurement perspective. This interoperability ensures a comprehensive and triangulated understanding of marketing impacts, empowering advertisers to plan with confidence and precision.

Join the Revolution in OOH Advertising

The partnership between AdQuick and Keen represents significant differentiation of the level of actionability provided by measurement, offering advertisers a robust, predictive, and real-time optimization tool for OOH and omnichannel advertising.

Contact Keen today to qualify for a free demo and 10% discounted license to measure, plan, and forecast your media plan. Available for a limited time only.

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Crisp and Keen help CPGs get smart about media spend

Guest post by Samantha Johnston, Marketing at Crisp

The new partnership between Crisp and Keen Decision Systems helps CPG marketers understand the impact of full-funnel marketing: what’s working, what’s not, and how to optimize the next marketing dollars spent.

In today’s marketing environment, there are more ways than ever to reach consumers – and measuring the impact of marketing across retailers and ecommerce platforms is more challenging than ever. With so many options comes the need to know if you’re using your media resources wisely at the speed marketers need to make decisions. That’s why Crisp has partnered with Keen to help CPGs measure, plan, optimize, and forecast their omnichannel media investments.

Len Ostroff, EVP of Sales and Partnerships at Crisp, joined Keen founder and CEO Greg Dolan to discuss how the integration brings valuable tools to the modern marketer’s toolbox.

Retail marketing: More choices, more problems

As Dolan points out, there are thousands of marketing decisions that have to be made every week, or even every day, to allocate marketing resources.

Of course, today’s CPG marketers also have to justify every dollar they’re spending – and that’s where the fragmentation leads to even greater challenges. CPGs need to collect data from disparate channels, make sense of all that data, and ultimately try to determine the ROI of media spend.

On top of that, cookie deprecation means the industry must transition away from one-to-one targeting toward geo-based or cohort-based targeting – which makes connecting digital marketing to sales all the more complicated.

Adding retail data to the marketing mix

An informed retail marketing strategy requires retail data to measure the impact of campaigns across retail media networks and the open web online and in-store.

As Ostroff explains, retailers share a wealth of data with their suppliers, but there’s no standard format for how that data is shared from Walmart to Target to Amazon. “If you are a multi-retailer CPG, making sense of retail data for supply chain management, demand planning, assortment planning, media and marketing…. it becomes nearly impossible,” he says.

That’s where Crisp comes in: to make retail data accessible and usable for teams across the organization on a daily basis.

For marketing teams, that means the ability to quantify each of those dollars and the impact it’s having on the business. That’s what Keen’s decision-making system enables – taking in a range of inputs and turning them into actionable insights to inform future spending decisions. 

Crisp and Keen give brands the full picture

Together, Crisp and Keen can combine daily, store-level data from retailers with marketing mix modeling to guide future-focused decisions in real time.

For Keen, it’s not just about tying a campaign at a given retailer to sales at that same retailer, but understanding the interconnectivity between channels. “Finally, CPG organizations are starting to structure around omnichannel, which is helping them to look across all the different channels and the portfolio effects of a brand’s media investment,” Dolan explains.

While the analysis may be complex, the result is simple: brands can understand what’s working, what’s not, and where to spend that next dollar for maximum results.

To learn more about how Crisp and Keen can help your brand, contact the Crisp team or Keen team today. For more industry news and best practices, subscribe to the Crisp blog.

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DTC Marketing Mix Optimization: A Guide

Introduction to DTC Marketing

As the digital age continues to evolve, businesses are persistently seeking innovative ways to reach their customers. Direct to consumer (DTC) marketing stands at the forefront of these strategies, eliminating more traditional middlemen and creating a more intimate interaction between brands and their consumers. For brands navigating this terrain, understanding the fundamentals of direct to consumer marketing can be a game-changer. It’s an approach that allows a profound sense of connection and personalization, and as a direct to consumer brand, leveraging these advantages will undoubtedly create positive outcomes.

In the bustling digital era, where DTC brands are aggressively competing for consumer attention, understanding and implementing an optimized marketing mix can be a game changer. Marketing mix optimization helps brands to maximize effectiveness and efficiency in reaching and engaging your target audience. Let’s dive into how DTC brands can enhance their visibility and drive sales by fine-tuning these crucial elements.

Evolution of DTC Marketing Strategies

DTC marketing strategies have seen a monumental shift over the years. From the initial stages, where companies relied heavily on traditional advertising methods and direct mail, these strategies have evolved, incorporating the use of cutting-edge technology to achieve an unprecedented level of personalized, timely, and effective communications. This progression has served to redefine the purchasing experience for consumers, providing them with more choice, control, and convenience than ever before. Brands that operate on a DTC model are at the very heart of these transformations. This narrative explores the sequential evolution of DTC marketing strategies, to provide actionable insights that businesses can use to fortify their marketing game plan in this highly competitive sector. From the inception to the current age of digital marketing and eCommerce, it brings into focus the dynamic journey of DTC strategies and highlights the key trends shaping the future.

Importance of Cross-Channel Optimization for DTC Brands

Cross channel optimization is of utmost importance for DTC brands. With the proliferation of various marketing channels such as social media, email, websites, and mobile apps, it is crucial for brands to have a seamless and consistent brand experience across all platforms. By optimizing the messaging, timing, and targeting across different channels, DTC brands can ensure that their customers receive a cohesive and personalized experience. This not only enhances customer satisfaction but also increases brand loyalty and generates higher conversion rates. Cross channel optimization allows brands to reach customers at different touchpoints, maximizing their exposure and ultimately driving business success.

Role of Marketing Mix Modeling (MMM) in DTC Success

Marketing mix modeling plays a crucial role in the success of DTC brands. It enables companies to analyze the impact of various marketing elements, such as product, price, promotion, and distribution, on key performance indicators like sales and customer acquisition. By quantifying and understanding the influence of each element, DTC brands can optimize their marketing strategies to increase effectiveness and efficiency. Marketing mix modeling provides valuable insights and data-driven decision-making, allowing brands to allocate resources wisely, identify underperforming areas, and capitalize on successful tactics. Ultimately, it helps DTC brands achieve their marketing goals, generate revenue, and gain a competitive edge in the ever-evolving consumer market.

Keen's Approach to Holistic Measurement and Optimization

Due to the increase of new on and offline channels appearing on a regular basis, a DTC marketing mix optimization needs to take a holistic measurement approach. Keen’s SaaS based marketing mix platform provides historical performance measurement, as well as predictive and prescriptive plans to optimize ongoing marketing spend decisions—across all channels including retail media and ecommerce. Those investment decisions are then connected to financial outcomes

Our Bayesian modeling approach combines multiple sources into a unified model. Our models are sourced with the following data:

Historical MeasurementKeen's Knowledge Estate (Marketing Elasticity Engine)Prior Brand Studies
Includes your weekly revenue, activity by channel and platform, marketing investments and external factors such as relative price and distribution.Includes 40 years of academic models.Includes tactic coefficients from prior MMX studies, internal analyses and panel data, household penetration data and lift studies.
Calculates base revenue and marketing influenced revenue, then quantifies impact of each marketing dollar.Includes 10 years of client metadata and data from recent marketplace dynamics. Data includes industry and category, size of business and lifecycle and margin, geographic location and region and distribution channels (online, offline and both) and many more.
Measures the equity effect of current revenue (long-term ROIs).Can act as custom priors for your brand which can be influenced through the regression model when your data is loaded in. Data can include clicks, time series spend, impressions, COGS, etc.

From these three types of data brands receive a holistic measurement model they can use to accurately plan future investments.

The Impact of MMM on Short-term and Long-Term Marketing Goals

Marketing mix modeling is a powerful analytical technique that helps businesses understand the impact of their marketing efforts on short-term and long-term marketing goals. By examining the various elements of the marketing mix , this modeling approach provides valuable insights into the effectiveness of each element and their collective contribution to achieving marketing objectives.

In terms of short-term goals, marketing mix modeling helps businesses make data-driven decisions to optimize their marketing campaigns. By analyzing the impact of different marketing activities on sales, customer acquisition, and brand awareness, companies can allocate their resources more effectively and target their efforts towards the most impactful channels and strategies. This enables businesses to generate immediate results, improve their return on investment (ROI), and drive short-term revenue growth.

On the other hand, marketing mix modeling also plays a crucial role in shaping long-term marketing strategies. By understanding the long-term effects of different marketing activities, companies can make informed decisions regarding product development, pricing strategies, and brand building. By identifying the drivers of long-term success, businesses can focus on creating sustainable competitive advantages, building brand equity, and fostering customer loyalty. This approach helps companies plan for the future and ensure long-term profitability and success.

MMM is an invaluable tool for businesses looking to achieve both short-term and long-term marketing goals. It enables data-driven decision-making, optimization of marketing campaigns, and the development of effective long-term strategies. By leveraging these insights, companies can achieve sustainable growth and stay ahead in a competitive market.

Expanding Beyond Performance Marketing (Digital Media) with Keen

Over the past decade, Performance Marketing has become the norm in the marketing landscape, focusing on metrics like Return on Ad Spend (ROAS). However, blind reliance on ROAS can hinder the growth of performance marketers. To overcome these limitations, a shift towards Incremental Return on Ad Spend (iROAS) is needed. iROAS considers a broader range of factors, including non-impression-based media and macro conditions that may impact sales. It emphasizes incremental returns, providing a clearer picture of marketing’s impact. Marketers must reevaluate their key performance indicators and adopt a more nuanced approach. Tools like Keen can help measure the long-term effects of marketing tactics, enabling informed decision-making and bottom-line impact.

Data-Driven Decision Making with the Keen Platform

The Keen Platform is designed to become part of the planning process at every stage. 

It allows you to see the effect of marketing spend across all channels, and how they impact each other. You have the ability to evaluate channel and timing options, and quickly account for how your marketing decisions contribute to or distract from your targeted financial outcomes. Our models adapt and evolve over time, ensuring relevance and accuracy providing DTC brands with data they need to make their next investment decision.

Personalizing the DTC Customer Experience Through Data Analytics

Personalizing the direct-to-customer experience through data analytics is a game-changer for businesses. By leveraging customer data, such as purchase history, browsing behavior, and preferences, companies can create tailored and relevant experiences. Data analytics allows businesses to understand individual customers on a deeper level, enabling targeted marketing campaigns and personalized product recommendations. Through personalization, businesses can enhance customer satisfaction, increase engagement, and drive repeat purchases. By utilizing data analytics, companies can unlock valuable insights to deliver a personalized experience that delights customers and builds long-lasting relationships.

Implementing Effective DTC Marketing Tactics with Keen

The Keen Platform enables marketers to see the potential ROI on investments in new channels before you start testing and presents the optimal plan to hitting your revenue goals.

Additionally, the platform will optimize the interaction effects between on and offline channels and timing impact to drive the most profitable result for your brand.

Maximizing DTC Marketing Mix Efficiency with Keen

Maximizing efficiency in your DTC marketing mix is not just about leveraging the right tools and technologies but also about making informed decisions based on accurate, predictive insights. The Keen Platform is a powerful solution that empowers marketers to navigate the complex landscape of DTC strategies with confidence and precision. By integrating data-driven insights into every facet of your marketing strategy, businesses can identify the most effective channels, optimize their spending, and achieve a higher ROI. The roadmap to a successful DTC marketing strategy is intricate and ever-evolving, yet with Keen, marketers can unlock unparalleled efficiencies and drive sustained growth.

Want to learn how Keen can help you embrace the power of data and analytics to transform your DTC marketing efforts? Take a tour of the platform today!

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The Hidden Pitfalls of ROAS: How it’s Killing Performance Marketers

Evolution of Performance Marketing

Over the past decade, the marketing landscape has witnessed a shift with the rise of Performance Marketing. The focus on low-funnel attribution and deterministic metrics, such as Return on Ad Spend (ROAS), has become the norm. However, the blind reliance on these metrics may be detrimental to the growth and success of performance marketers. Let’s explore the limitations of ROAS and advocate for a more nuanced approach – Incremental Return on Ad Spend (iROAS) – as the true North Star for measuring marketing performance analysis.

Limitations of Deterministic Attribution in ROAS

ROAS relies heavily on deterministic attribution, connecting ad impressions to conversions using identifiers like IP addresses, cookies, or click IDs. While this method seems straightforward, it has several inherent limitations.

Not All Media Transactions are Impression-Based

Media channels like email, SMS, or outbound call centers operate outside the impression-based model. ROAS fails to capture the effectiveness of these channels, limiting the scope of performance measurement.

Challenges of Log Level Data in Performance Marketing

The reliance on log level data, a comprehensive spreadsheet detailing impression attributes, is another constraint. Not all platforms or walled gardens share this data, creating blind spots in the performance measurement process.

Causality vs. Correlation

ROAS struggles to differentiate between causality and correlation. Did an ad truly influence a conversion, or would the action have occurred regardless? This distinction is crucial for accurate a marketing performance analysis.

Introducing Incremental Return on Ad Spend (iROAS)

To overcome these limitations, the marketing industry needs to shift its focus from ROAS to Incremental Return on Ad Spend (iROAS). This approach considers a broader set of factors, acknowledging the complexity of marketing ecosystems.

Inclusive of Non-Impression-Based Media

iROAS accommodates channels beyond impressions, providing a holistic view of marketing performance. Email campaigns, SMS, and outbound call centers are given due consideration in this more comprehensive measurement model.

Factors in Macro Conditions

Beyond deterministic attribution, iROAS considers macro conditions that may impact sales. Events like Cyber Week or Prime Day can artificially inflate ROAS without necessarily reflecting the effectiveness of marketing efforts.

Emphasizes Incremental Returns

Unlike ROAS, which may mask declining sales with seemingly positive returns, iROAS focuses on incremental returns. This metric provides a clearer picture of the true impact of marketing efforts on the bottom line.

The Need for a Paradigm Shift: From ROAS to iROAS

It’s time for marketers to reevaluate their key performance indicators. Shifting from ROAS to iROAS requires a recalibration of measurement tools and strategies. Advertisers must embrace a more nuanced approach to performance marketing, acknowledging the interconnectedness of various channels and external factors.

In platform vs. Unified ROAS Tools

Each platform reports on ROAS in it’s own silo, with no regard to the overlap between channels. In fact, they’re incentivized to do so, since most of their earnings are ad-driven, and more effective ads (per their reporting) leads to more ad dollars. Thus there’s been an emergence of holistic attribution reporting. In other words, platforms that answer the question, “What’s my ROAS across everything, considering the overlap between the channels I run media on?” While unified ROAS tools solve the in-platform ROAS and interaction effects issue, they still fall into the deterministic traps mentioned above. For instance they’ll report higher unified ROAS during Black Friday for e-commerce brands, the implication being that their marketing is working better during this time, when the reality is that much of the revenue going into that ROAS calculation comes from sales that would have happened anyway simply because it’s Black Friday and people are shopping online, not because of any specific marketing effort.s. True success lies in adopting a model that encompasses a broader spectrum of variables, ultimately guiding marketers towards impactful decision-making.

That is where Keen comes in.  The Keen Platform uncovers key insights that help marketers tie both short-term transaction driving tactics and long-term brand building investments directly to the financial outcomes of the business, empowering them to make data-driven future decisions.  This is done by:

  • Aligning sales and marketing data over time
  • Accounting for prior brand knowledge and external factors that impact marketing
  • Isolating incremental vs. base volume, and quantifying the incremental for each tactic
  • Compare incremental revenue driven by each tactic to the the investment in that tactic to determine profitability
  • Leveraging this knowledge to inform scenario building for future decisions

In the graphs below, you can see how the Keen Platform accounts for the long-term value of marketing, for channels that are brand-building and transaction-driving. 

Additionally, the graphic below shows a holistic view of marketing on all quarters. As you will see, for this brand, marketing from 2020, 2021, and 2022 continued to pay dividends in 2023 – representing the way marketing layers like rock. This view allows marketers to evaluate marketing’s sustained impact on business growth, across all channels.

Although ROAS was once hailed as the holy grail of performance metrics, it is proving to be a double-edged sword for marketers. To thrive in an ever-evolving landscape, performance marketers must embrace Incremental Return on Ad Spend as the new North Star and a tool like Keen can help marketers measure the long term impacts of these kinds of tactics. By doing so, marketers can unlock a more accurate and holistic understanding of their marketing efforts, enabling them to make informed decisions that truly impact the bottom line. 

Want to see for yourself how Keen can create a marketing performance analysis for your business?  Take a tour of the platform today!

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Why your SME is not too “Small” for Marketing Mix Modeling

Introduction to Marketing Mix Modeling for SMEs

Marketing mix modeling (MMM) is a contemporary statistical tool that empowers marketers to quantify the impact of several marketing inputs on sales or market share. With MMM, a brand can streamline its marketing efforts and direct them towards the right audience, at the right time and investment level.

MMM is an accessible, predictive marketing analytics tool for companies of all sizes. MMM has historically been viewed as a tool used by large enterprise companies due to its high cost and large team size needed for implementation. In this guide we will discuss why Keen’s MMM tool is accessible for small and medium-sized enterprises (SMEs) and how it is revolutionizing marketing teams within these companies.

Automation of Data Collection

In our dynamic marketing environment, the automation of data collection has become a cornerstone for efficient data management and insightful analysis. It’s a critical component of marketing mix modeling that helps to understand and manipulate multiple marketing variables.

Reduces Workload

Automation significantly lightens the workload and reduces time spent on manual data collection, minimizing the need for extensive team involvement. It also decreases the potential for human error. This efficient system ensures that businesses can focus on key aspects that demand strategic attention, like cross-channel marketing optimization, rather than data gathering. This marketing efficiency improvement results in both time and cost savings.

The Benefits of Bayesian Modeling

Keen’s utilizes Bayesian marketing mix modeling techniques. These methods leverage prior estimates of tactic elasticity and continuously learns from new data. This approach results in a model that adapts and evolves over time, ensuring relevance and accuracy.

Some additional benefits of Bayesian modeling for small to medium enterprise companies include:

Incorporates Prior Knowledge: Bayesian modeling allows marketers to incorporate prior knowledge or beliefs into the analysis. Prior knowledge can include ROIs from previous campaigns, results of brand studies or any other data you think is relevant to help understand your business. This is especially useful when there is existing information about the effectiveness of certain marketing channels or when there are strong assumptions based on industry expertise.

Handles Small Sample Sizes: MMM may face challenges when dealing with limited data. Bayesian methods can handle small sample sizes more effectively by incorporating prior distributions, helping to provide more stable estimates even with limited data.

Accounts for Uncertainty: Bayesian models naturally provide a framework for expressing and quantifying uncertainty. This is particularly important in MMM, where there can be various sources of uncertainty, such as seasonality, market dynamics, and external factors. Bayesian models provide credible intervals that give a range of likely values for the model parameters, providing a more nuanced understanding of the results.

Flexibility in Model Complexity: Bayesian modeling allows for the incorporation of complex relationships between variables. This flexibility is beneficial when dealing with a diverse set of marketing channels and intricate interactions between them. The model can be adjusted to capture nonlinearities and interactions more accurately.

Dynamic Updating: Bayesian models can be easily updated as new data becomes available. This is crucial in marketing, where the effectiveness of channels and campaigns can change over time. Bayesian methods allow for adaptive learning and continuous improvement of the model as new information is gathered.

Probabilistic Outputs: Bayesian modeling provides probabilistic outputs, allowing marketers to make decisions based on the likelihood of various scenarios. This can be valuable for risk assessment and decision-making in marketing strategies.

Ideal for teams with limited resources

These efficiencies make it an excellent fit for marketing teams with limited resources. Marketers can extract maximum insights from their existing data, fostering smarter, data-driven marketing strategies and decision-making without the need for extensive data collections or complex infrastructures.

In addition to this technique, we also bring our patent-pending Marketing Elasticity Engine as our knowledge estate.  This acts as our custom priors for your brand, which can be influenced through the regression model when we load in your knowledge estate (time series spend, clicks, impressions, COGS, etc).

Scalability and Adaptability of MMM

Scaling your brand to new heights requires a flexible marketing technique – one that transforms as your business objectives grow. Marketing mix modeling is scalable and dynamic in nature. It proves to be immensely beneficial for businesses focused on escalating their market presence.

Adapts as your team and budget grows

It flexibly adapts to your budget and team’s capacity. Whether you have a big marketing budget or you’re operating with less, marketing mix modeling:
– Customizes your marketing strategies based on budget constraints
– Efficiently executes these strategies with a fluctuating team size
– Optimizes your marketing efforts, ensuring maximum ROI

Gaining a Competitive Edge through MMM

The true value of effective marketing mix modeling can be realized in achieving a significant competitive advantage. By understanding the varying components and the interplay among them, a brand can make its marketing activities more effective.

Marketing Efforts More Targeted and Effective

Comprehending the interactions among different components of the marketing mix enables a targeted approach. For example, to better allocate your budget, a model will identify where and when money should be spent for maximum impact. Or, if you are looking to predict future outcomes, the model will provide an understanding of the impact of different variables can help in anticipating future market behavior.

Leads to Higher Returns That Justify Initial Investment

Keen’s marketing mix models lead to increased efficiency, improved return on investment, potentially contributing to substantial growth – all of which justify the initial investment required.

Cost Effectiveness of MMM for SMEs

Cost effectiveness is the focus of companies, regardless of size. Marketing technology for SMEs must be cost-effective because it is imperative that an investment in a marketing mix modeling solution will show a return in efficiency and effectiveness.

Keen’s affordable pricing structure is designed to provide SMEs with a cost-effective marketing analytics tool with a variety of purchasing options to meet their needs.

The Accessibility of MMM for All Business Sizes

In conclusion, marketing mix modeling (MMM) is a data-driven tool that is now available for companies of all sizes, including SMEs. 

Benefits of Keen's MMM solution
Platform featureBenefit to SMEs
Automated data collectionLess internal resources required
Uses Bayesian methodologiesProvides accurate results with limited data
ScalableAdjusts to the team's size, budget and aligns with growth objectives
Makes marketing more targetable and effectiveAllows you to gain a competitive advantage
Cost-effective solutionAffordable and allows teams to work more efficiently and effectively

Start your model today! 

240205_Keen_BP_3Cs

Guide to Decision Making with Unified Marketing Measurement

You can’t measure your way to a decision.  If you’re building a house, you have to start cutting and hammering, at some point, even if after measuring twice.  And so it is with making decisions, you might measure twice, but at some point you’re going to make a decision, develop and deploy the marketing budget.

Making Decisions with Unified Marketing Measurement

Developing marketing budgets is difficult. Marketing and finance professionals are constantly challenged to find the right mix and level of investment to drive topline revenue growth and maximize profits.  Budgeting is a constant negotiation that exists in every organization.  Even when there’s an explicit annual planning cycle, there are invariably those critical moments when the situation changes for better or worse and marketing budgets along with revenue forecasts need to be revised. 

Unified marketing measurement holds the promise of providing a structured approach to tackle these challenges, providing a framework that helps with making trade-offs between revenue targets and investment, across multiple marketing tactics.  However, realizing that promise is challenging and far from guaranteed. 

In this article, we will explore the factors that make marketing investment decisions difficult, how marketing mix models can help or hinder the process, and some tips for avoiding common pitfalls.

Navigating the Three C’s: Complexity, Conflict and Cost

Why is this so difficult?

At the heart of the challenges lie Three C’s – Complexity, Conflict, and Cost – each representing a hurdle that marketers must overcome to make marketing investment decisions that achieve results.

ComplexityConflictCost
Multiple products
Multiple investment alternatives
Multiple marketing tactics
Multiple target/geos
Non-linear effects
Present vs future
Uncertainty
Ambiguity
Different people
Different objectives
Different theories/frames
Different information
Competition for resources
Personal objectives
Organizational misalignment
Data acquisition
Knowledge management
Access and retrieval
Modeling and analysis
Opportunity identification
Storage/retention
Misinformation

Complexity means analytical and logical complexity.  With a marketing mix it’s like untangling a big hairy ball.  Think about the sheer breadth of variables in play – multiple distribution channels, diverse product segments, varying geographic markets, and a plethora of marketing tactics.  And then you layer on the fact that there are diminishing marginal returns to investment, so that the incremental returns, while positive, decline when investment amounts increase.  And there are different effects over time: short-term vs long-term. 

All this complexity in marketing means that there are a lot of different ways to conceptualize this problem, logically and analytically.  Marketers and analysts alike are immediately confronted with lots of ambiguity that stems from the multitude of ways to conceptualize and quantify the effect of marketing.  Further, most marketing mix models are trying to quantify all this using historical data, which is imperfect.  Imperfect data yield potentially biased and uncertain results.

Conflict often surfaces within the organizational structure itself.  Marketing teams, armed with varying perspectives and vested interests, may have differing views on the optimal path forward. This conflict extends to strategic objectives, priorities, and the allocation of resources.  Balancing these conflicting viewpoints requires not only strategic acumen but also a keen understanding of interpersonal dynamics.

Put yourself in the seat of the manager responsible for the decision.  They have multiple different people coming to them, each of them responsible for different tactics, products, etc., and each having a different logical understanding of the problem, and a different information set and analysis.  And of course, each responsible person makes the case for investment in their tactic. 

Now the decision maker must evaluate all of that, and as they do, they also invariably are not just making trade-offs between tactics and investments, but also making trade-offs on information quality, and between the people themselves.  This leads to a lot of conflict.

Costs are driven by the resources expended in analyzing data and modeling scenarios, underscoring the need for judicious and focused analytical efforts.  Both Complexity and Conflict push managers and analysts to an endless pursuit of certainty out of fear for making the wrong decision.  Decision-makers and analysts incorrectly assume that certainty exists, if only they had the right data.  This means that managers and analysts can run up the tab analyzing the data and trying to find the right model to put it all together.

Together, these Three C’s challenge marketers to devise strategies that are analytically sound, organizationally aligned, and financially prudent.

The Role of Marketing Mix Models

Marketing mix models can play an important role in wrangling the Three C’s.  To do so, marketers and analysts alike need to understand the role that the model plays in the decision process.  The entire decision process can be imagined like a decision-maker sitting on a stool.  The decision maker sits on the stool with furrowed brow and makes their decision.  The stool is the model.  It supports the decision-maker through the process.

When the model is properly built it supports the decision even under the weight of the heaviest of decisions.  However, if not properly built the model crumbles and leaves the decision-maker to their own devices.  And so, building the model well is fundamentally important.

To support the decision, the model must be built with the decision-maker in mind.  In the end, the model should be an extension of the decision-maker’s considerations, objectives, values, alternatives and information. 

Understanding the Frame in Marketing Decisions

It all starts with what we, at Keen, call the Frame.  The Frame captures the presuppositions.  It’s the ground on which the stool sits.  We like to think about this in terms of what is in play.  What tactics should be considered for the decision, and what factors are necessary to account for in the analysis. 

In the end, we want to be able to think about the model as a representation of the drivers of sales.  To achieve this goal, it is fundamentally important that the model account for the most important known causal factors in sales including but not limited to seasonality, holidays, price, distribution and supply, product changes, competition, economy, and of course marketing investment.  At Keen, users in the Keen Platform start the process by naming all these factors and tag them as either Decision Factors or Environmental Factors. 

A good Frame ensures that when it comes time to decide, all the factors that need to be expressed as drivers, outcomes, and alternatives are included in the decision.  The Frame is the ground floor underneath the model. 

The model itself must, therefore, translate all the factors into values that the decision-maker can compare and trade-off when comparing alternatives.  A marketing mix model may provide sales forecasts, ROIs and forecasts of any other non-financial metrics like awareness.  At Keen, we focus on the financial value of the marketing decisions because a dollar speaks like no other language.  The model in the Keen Platform yields both a revenue forecast and contributions.  Contributions are converted to cash flows from marketing investments and forecasted into the future.  The marketing-driven cash flows are discounted based on how far into the future they occur and then totaled in a metric we call the Net Present Value of Marketing Investment (NPV).  NPV captures both the short-term and long-term value of marketing in a single metric. 

Last, but not least, it’s important to use the best information available and use the best methods for the available information.  The operative word is available.  As discussed above, in pursuit of certainty, too many analysts focus on using the “best” methods.  Statistically speaking, the best method means a randomized controlled trial (RCT).  Typically, large-scale RCTs are off limits due to the cost and operational requirements in their execution.  The requirement to control the treatment, means that they are almost always limited to a single tactic, campaign and execution.  This very restricted RCT is what people often call A/B testing.

Marketing mix models, because of their need to support the frame of the decision maker, need to be unified, meaning that they need to capture the range of the tactics influencing sales.  This means that we need to have a common method that is appropriate for all the tactics under consideration in the decision. 

In traditional approaches, the burden placed on the data to measure all the factors necessary to a unified decision is too high.  The data are just not up for it.  Even when the data are captured at the lowest levels of observation available, the burden to account for all the factors, measured and observed at different levels, and especially unobservable factors is too great.  And so, we must abandon methods that focus only on the observational data.

Thankfully, organizations do conduct A/B tests, and they have direct observations from attribution studies, and they have a team of experienced professionals that include managers, agencies, and consultants.  There is every reason for a decision-maker to rely on the information available from them.  This is what we, at Keen, call the Information Estate. 

To integrate the full Information Estate, users in the Keen Platform leverage a Bayesian estimation approach, which integrates the Information Estate with the observational data.  This is effective in handling many of the problems that arise from observational data on marketing including sparsity, low variation and multiple correlation.   

Nate Silver, in his book, The Signal and The Noise, does a great job of demonstrating the value of Bayesian methods for many different disciplines including applications to popular topics like politics and baseball.  Every day you read your email your spam filter is using Bayesian methods to constantly revise its understanding of which emails go to your inbox versus junk.  And Bayesian methods are guiding all sorts of autonomous things from vacuums to vehicles and drones to moon landers.

The Significance of Bayesian Estimation

The Bayesian approach, when done properly, also has the benefit of providing transparency to the information in the model so that all stakeholders understand and trust the inputs and outputs.  At Keen, users in the Keen Platform, use Bayesian marketing mix modeling methods so that the model can learn from other sources of information about ROIs.  Users can provide ranges of ROIs from multiple sources to be used in the model.  ROIs are a user-friendly and transparent way of expressing information about marketing effectiveness in what may otherwise be a highly technical conversation about coefficients. 

For the interested reader, credits to Howard Raiffa and Ronald Howard for their developments in the field of decision analysis.  The framework used above is based on the Decision Quality framework used by practitioners of decision analysis. 

Common Pitfalls in Marketing Mix Modeling

For all the benefits and promise, marketing mix models can crumble under the weight of the decision.  When this happens, it causes the decision maker to resort back to using their own and less-informed mental model.  It also leaves everyone involved in the process to wonder why they expended such effort, time and money to go through the process.  We commonly see three reasons why marketing models fail: mismatched frame, improper use, and missed timelines.

Mismatched Frame occurs when the decision maker desires to make a decision about a tactic that is not in the model.  This commonly occurs when there are new tactics under consideration.  For example, imagine a manager who wants to invest in television for the first time after having previously invested in digital tactics such as paid search.  It’s common for marketing mix analysts to restrict their model to only the historical data, rather than the frame for the future decision.  In other words, the model is framed in service of the historical data rather than in service of the decision maker. 

A closely related cause for mismatch is that the statistical analyst, desiring to follow statistical practices, will remove variables from the model that are not “statistically significant” according to the data.  If there has not been any discussion with the decision maker about the frame, then removing this variable will limit the possible frame.  In this case, the analyst relying on the data, is creating the decision frame rather than relying on the decision maker for the frame.

Further, it’s possible for estimates from the model to defy the logical expectations of the tactics.  For example, it’s common for some marketing estimates to be negative when there are problems with multiple correlation or for other reasons for price to be estimated as positive.  If left in the model, these results can oppose common knowledge and more importantly, oppose the prevailing mental model of the decision maker.  If removed from the model, then this can lead to the frame mismatch problem.

Improper Use occurs when the model is used in a way that does not match the natural conclusions of the model.  The most common cause of this is reliance on ROIs and Contributions as metrics to inform future decisions.  It’s important to understand that Contributions from marketing mix models provide the decision maker with an estimate of the difference between investing at a given level and investing nothing.  ROIs typically reflect a translation of Contributions and Investments into financial terms.  Literally, ROIs provide an estimate of the value of investing at the simulated level versus investing nothing.  This implies that the only two choices are investing at the simulated level and investment nothing, which does not express the idea that investments can be incrementally increased or decreased. 

Expanding further, if the decision maker were to consider investments at lower or higher levels, they would be left without information from ROIs or Contributions alone.  Unfortunately, many decisions are erroneously made assuming that the stated ROI holds up for any level of investment.  If the ROI is low the tactic might be cut all together or, if high, seen as a blank-check endorsement for more investment at any level.  Both are erroneous conclusions because they ignore the fact that marketing investments have continuous and diminishing marginal returns.  ROI-based decision rules ignore the knowledge that returns increase by spending less and decrease by spending more, and that there exists a financially optimal investment for each tactic. 

Missed timelines happen with marketing mix modeling projects when those involved in the effort fail to appreciate all the problems with Complexity, Conflict, Cost, and all the ways in which marketing mix models can fail.  This leads to endless iteration and rework.  Many marketing mix modeling projects are planned to be eight-week efforts only to turn out to be sixteen-week slogs.

One of the hidden costs to timelines, especially with those who focus on the statistical modeling aspects, is ambiguity.  As a part of the upfront marketing data analysis and collection effort, there is typically a lot of ambiguity in the way that certain tactics are defined and monitored.  For example, is Influencer a tactic unto itself or is it a social media tactic?  What does it mean to invest in Influencer tactics?  Just wrestling these questions to the ground can take a week by the time all the people are consulted.  Further, these questions may not even be raised until after the first iteration of the model is completed. 

How does traditional mix help?

ComplexityConflictCost
Multiple products
Multiple investment alternatives
Multiple marketing tactics
Multiple target/geos
Non-linear effects
Present vs future
Uncertainty
Ambiguity
Different people
Different objectives
Different theories/frames
Different information
Competition for resources
Personal objectives
Organizational misalignment
Data acquisition
Knowledge management
Access and retrieval
Modeling and analysis
Opportunity identification
Storage/retention
Misinformation

Best Practices to Avoid Modeling Pitfalls

It’s clear that marketing mix modeling not only holds great promise as a unified approach, but also poses great challenges.  The road marketers travel is littered with marketing mix models that have gone wrong.  So, it’s important to understand some steps to take to avoid the pitfalls. 

Start with establishing the frame.  When establishing the frame, it’s important to embrace the frame of the decision maker.  Identify the person or group in the organization that is responsible for making the marketing investment decisions and make sure the outcome measure, tactics to be decided, and all the other drivers of that outcome measure are included in the model.  Ask the decision maker to think forward with you and play out some of the alternatives they might consider and ask questions to get behind the whys.  As advocated by Judea Pearl in his book, The Book of Why, developing a causal graph with arrows pointing in the direction of the causal influence between the different factors expected to be in the model is helpful.  This exercise will support a conversation about the frame and level-set the model early in the process. 

Be a Bayesian.  Embrace the Bayesian way of thinking about statistical analysis.  These days most machine learning algorithms employ some kind of Bayesian estimation procedure, but there’s more to this than just the algorithm.  Embrace the idea that the data are limited in their ability to fully inform the model.  Spend time thinking about how the modeling process can leverage all the available information including previous studies, meta-analyses, and even the experience of the decision maker.  A good marketing mix model will support a decision, rather than produce a metric.  Decisions are ultimately made by people, and so it’s helpful to take the perspective of the decision maker and their organization when informing the model.

Use software.  The Three C’s, the data, estimation processes, and pitfalls are just too intricate to leave this to a bespoke effort.  Using software will help tame ambiguity and complexity.  As discussed above, at Keen, users in the Keen Platform go through a process of enumerating and naming all the factors in their model.  The Platform walks users through a process that provides definition and removes ambiguity.  Further, users in the Keen Platform take a Bayesian approach.  Where they have information in their knowledge estate, they can provide it as an explicit transparent input to the model.  And finally, The Platform does the heavy lifting of estimating the model, calculating metrics, forecasting revenue, and calculating NPV.  These are all complex calculations that involve simulation from the model, some calculus and financial math.  All happens in seconds, keeping the user focused on the support decisions.

Keen Platform addresses pain points

ComplexityConflictCost
Multiple products (Portfolio)
Multiple investment alternatives (Plans)
Multiple marketing tactics (Factors)
Multiple target/geos (Portfolio)
Non-linear effects (Model)
Present vs future (Long-term/NPV)
Uncertainty (Risk/Monte Carlo)
Ambiguity (Notes, Naming, System)
Different people (User roles)
Different objectives (Plan optimization)
Different theories/frames (Plans, Priors)
Different information (ROIs-to-Priors)
Competition for resources (Financial analysis)
Personal objectives (UX)
Organizational misalignment (ROIs-to-Priors, Plans, Roles, System)
Data acquisition (MEE, Connectors, Data Proc)
Knowledge management (System)
Access and retrieval (System)
Modeling and analysis (Model, Plans, Reporting)
Opportunity identification (Plans)
Storage/retention (System)
Misinformation (Forecast validation, Transparency)

Conclusion

Unified Marketing Measurement stands at the forefront of revolutionizing marketing investment decisions, offering a beacon of clarity in the often-tumultuous sea of complexity, conflict, and cost.  At Keen, the true power is unlocked not by merely estimating a model, but rather through a deep understanding of the strategic role the model plays in supporting the analytical decision-making process.  By anchoring our  models within a well-defined framework, embracing the richness offered by a Bayesian approach, and harnessing our advanced software tool, marketers can transcend the common pitfalls that beleaguer less informed strategies. In doing so, it becomes more than a model—it transforms into a compass that guides marketers toward making more informed and impactful decisions, thereby ensuring that every marketing dollar is an investment towards a more profitable and insightful future.

To learn more about how Keen is helping teams make better decisions with our  tool and how we can help support your next marketing decision, start your model today.