Tag Archives: Laura Patterson

Creating a Marketing Performance Management Policy

Today’s marketers are under relentless pressure to obtain data, prove ROI and justify decisions. Marketers even have to go so far as to justify choices that haven’t been made yet, hence the momentum behind predictive analytics. It would seem we are in the the singular pursuit of measurement. So far this year, at every conference, event and customer meeting I’ve attended the question of ‘How do we show ROI?’ has surfaced.

Many marketers we work with have functional responsibilities and therefore their measures often reflect their role. As a result, the measures are frequently independent of each other and it’s difficult for marketing to truly demonstrate its impact and value. For example, social media marketers may be measuring mentions, sentiment, or traffic back to the website (hopefully you have moved beyond likes, and followers as your core metrics of success). Website/content marketers may be measuring the most popular pages or content downloads (hopefully you have moved beyond number of new items posted to the site in some period). SEO marketers may be measuring traffic and search engine ranking (hopefully you have moved beyond pages indexed or the number of backlinks). Email marketers may be measuring open and delivery rates (hopefully you have moved beyond counting the number of campaigns deployed). Asking the question, ‘How to measure the ROI of these tactics?’ is the wrong question. Read More…

Creating a Customer Engagement Metric

More than ever, marketing is under pressure to help acquire and retain customers while operating within tighter budgets. At the same time, customer engagement is emerging as an important concept as customers increasingly interact with companies across many channels. Higher customer engagement is seen as an indication of the emotional connection with the brand which correlates with business success.

A better customer experience is becoming an increasingly important way to differentiate for companies. Customer engagement plays a large role in the overall customer experience. We believe that customer engagement will continue to rise in importance as competition increases and switching costs decrease. With engagement becoming a key behavioral indicator, organizations will need to be able to link points of customer engagement with bottom-line improvements. Read More…

VEM and ITSMA Provide Marketing Data, Analytics, and Metrics Benchmarking Opportunity

Marketers who have come to be perceived as value generators for their organization have learned how to use data, analytics, processes and metrics to move business results and demonstrate their contribution. The problem is that many marketers are tracking metrics that are easy and convenient but have little or nothing to do with the organization’s performance. The real challenge for a good number of marketers is to develop and use metrics that drive results.

ITSMA and VisionEdge Marketing have teamed up in an Marketing Performance Mangement survey (open until July 27th) to give marketers the opportunity to gain insight in their use of marketing data, metrics, and analytics to inform marketing decisions, predict buyer behavior, improve marketing performance, and forecast trends.  Read More…

Four Parameters for Selecting Marketing Metrics that Matter

With the increased pressure on business leaders to be more personally accountable for the performance and conduct of their organizations, the emphasis on performance management has trickled down and across the organization, including marketing. Performance management focuses on optimizing individual or group performance in order to achieve the organization’s key initiatives and objectives. Performance management includes the metrics and the data, measurement, alignment and analytical processes, methodologies, capabilities and systems needed to manage the performance of an organization. A sound marketing performance management process is essential for enabling marketing professionals to demonstrate and communicate marketing’s impact on and contributions to the organization.

Marketing measurement provides the process for being able to measure marketing performance. When we wrote our second book, Measure What Matters: Reconnecting Marketing to Business Goals, we emphasized that just because we can measure something doesn’t mean that it matters. Since the book’s debut in 2004, the content that marketing can measure has only proliferated. Focusing on metrics that are easy may give Marketing interesting things to report, but may not help us demonstrate our value, foster better decisions or enable course corrections. The whole point of performance management, marketing accountability and marketing measurement is to help Marketing optimize performance and achieve meaningful business results. Read More…

Seven Key Steps for Creating a Performance-Driven Marketing Organization

Members of the leadership team expect marketing to generate value for their organization. Why? For many organizations, over 80% of their value is derived from intangibles. These intangibles, such as marketplace position and customer relationships, are often produced by marketing initiatives and result from marketing investments. Therefore, it’s no surprise that the leadership team’s expectations and pressure on Marketing will continue to rise. Generating value requires marketing to help the organization capture market share, increase customer lifetime value and grow customer equity. It is essential that Marketing maps out a clear direction and, as we say in Texas, ‘Get ’er done’. Read More…

Big Data Promises Marketers Big Insights

The amount of data being generated is expanding at rapid logarithmic rates. Every day, customers and consumers are creating quintillions of bytes of data due to the growing number of customer contact channels. Some sources suggest that 90% of the world’s customer data has been created and stored since 2010. The vast majority of this data is unstructured data.

It is not surpring, then, that study after study shows that the majority of marketers struggle with mining and analyzing this data in order to derive valuable insights and actionable intelligence. A recent report by EMC found that only 38% of business intelligence analysts and data scientists strongly agree that their company uses data to learn more about customers. As marketers we need to learn how to leverage and optimize this flood of data and incorporate it into customer models we can use to predict what customers want. Read More…

Optimizing Your Marketing Mix in a Multi-Channel World

Fifty years ago, optimizing the media mix was relatively easy. The channel mix was relatively manageable. Companies selected from a mix of national and local magazines, newspapers, broadcast television networks, radio and large industry trade shows. By the 90s, channel options became a bit more complex; with cable television, segmented direct mail and a bevy of trade publications and trade shows added to the mix. Today the media mix has exploded to include new digital channels such as social networks, SEO, online advertising, virtual events, email, and mobile. All of these marketing vehicles reinforce the importance of ascertaining the effectiveness and efficiency of your marketing channel investments; increasing the emphasis on marketing mix modeling and optimization.

What Is a Marketing Mix Model?
Marketing mix models are needed when you want to quantify the sales impact of various marketing activities and determine effectiveness and ROI for each marketing activity. Marketing mix modeling uses statistical analysis such as multivariate regressions on sales and marketing time series data to estimate and forecast the impact of various marketing tactics on sales. Regression is the workhorse for mix models. Regression is based on a number of inputs (or independent variables) and how these relate to an outcome (or dependent variable) such as sales or profits or both.

Once you have the statistics to create the model you can use these equations to figure out how to optimize your mix. This is known as Marketing Mix Optimization. You will want your model to account for direct as well as indirect effects and take things outside of your contract (such as the time of year, interest rates, exchange rates, gas prices, elections, competition, etc.) into account. Developing a marketing mix optimization model requires good data and strong analytical skills. You may find it prudent to partner with your finance organization to co-author the model. This will also help to generate a buy-in from the sales and leadership team.

When does it make sense to use a marketing mix model? For example, when you are trying to answers questions such as:

  • What happens if the economy changes by X?
  • What happens if we reduce/increase the marketing budget by Y?
  • What happens if the competition adds Z to their media spend or reduces their price?
  • What if we have to hold our touch points to the current mix, what is the optimal mix of these?
  • What is the optimal mix for our current budget?

However, the marketing mix model needs to support your overall organizational outcomes, marketing objectives, and metrics and performance targets. Optimizing a mix that will not enable you to achieve your outcomes and objectives may make you more efficient but will not make you more effective. If you are not meeting your performance targets or industry benchmarks, you may want to revisit your execution before you adjust your mix and spend.

How to Build a Marketing Mix Model
So you’re ready to build your model. What are the steps and what data will you need? Data is the key to being able to perform analytics. So the first step is to determine what data is going to go into your model. Common types of data include:

  • Monthly/Weekly sales data with causal factors
  • competitive information
  • monthly/weekly marketing spend by touch point (channel, promotion, etc)
  • customer demographic and other data
  • industry data
  • distribution data
  • product category data
  • economic and other data that impacts customer buying decisions

Things such as your data quality, the breath of internal and external data, the granularity of your data, the accuracy of your historical marketing data, the robustness of your statistical functionality, and the technical architecture to support the model construction all impact the quality of your model.

Optimizing Your Model
Once you have the data you can construct a prototype. Seven steps are important to finetuning your model:

  1. Test the predictive ability of the model on a hold out sample
  2. Refit using all the data and predict the future – remember to account for indirect effects and things out of your control in the model
  3. Compare actual to forecast sale performance and determine incremental revenue
  4. Apply financial data and determine ROI
  5. Model the influence of individual factors
  6. Simulate the impact of different marketing activities
  7. Develop and deploy the optimal marketing mix

We live in a dynamic environment and our channels are just as dynamic. Therefore, you will want to refresh your models quarterly and rebuild them at least annually. Building a marketing mix model may be one of those tasks worth outsourcing to the experts if you don’t have the analytical skills to develop your model or access to internal resources that can help.

Square up Your Data to Get Your Marketing Analytics Game On

Businesses tell us they believe in the concept of using analytics to drive decisions. Yet, a Bloomberg Businessweek Research Services study conducted earlier this year among 930 businesses across the globe in various industries, found that only one in four organizations believes its use of business analytics has been ‘very effective’ in helping to make decisions. Even though more than half of the companies in the survey said that they rely heavily on data and metrics when making decisions, many admitted that intuition and business experience still tip the scale when it comes to decision-making. Read More…

Brand vs. Business Marketers: Is Your Vocabulary Getting in Your Way?

We wouldn’t be surprised if you said, „what brand vs. business metrics?!” What’s wrong with these people, brand and business work together, not as opposing forces. And you are correct; the brand represents the promise of your business. The challenge is the C-Suites perception that marketers whose key performance metrics are primarily brand-related such as measuring awareness, relevance, and interest, are not in touch with the business. Read More…

Analytics and Marketing Operations: A One-Two Punch for Growth

Today’s customers are more value-oriented and less loyal, creating even greater challenges in today’s business climate.  With customer expectations increasing, the competitive landscape growing, the proliferation of new technologies and channels, and the avalanche of data, marketers needs more than intuition and experience to succeed.  The world is just too dynamic and the pace of change is just too fast.  In fact, the deluge of data is actually fueling the growth of analytics.  As Dave Frankland of Forrester once said, ‘the goal is not to collect data, but to develop insights.’ Insights are the purview of analytics.  Analytics are algorithms: advanced and/or mathematical techniques on large volumes of data that help marketers translate data into actionable insights to help drive marketing and customer strategies and optimize marketing efforts. Read More…