–Forecasting

1月 172018
 

Wherever there is uncertainty there has got to be judgment, and wherever there is judgment there is an opportunity for human fallibility. Donald Redelmeirer, physician-researcher Over the holidays, I read a fascinating book titled The Undoing Project: A Friendship That Changed Our Mind by Michael Lewis (W.W. Norton & Company, [...]

Why do we rely on judgment when analytics outperforms it? was published on SAS Voices by Charlie Chase

1月 172018
 

Wherever there is uncertainty there has got to be judgment, and wherever there is judgment there is an opportunity for human fallibility. Donald Redelmeirer, physician-researcher Over the holidays, I read a fascinating book titled The Undoing Project: A Friendship That Changed Our Mind by Michael Lewis (W.W. Norton & Company, [...]

Why do we rely on judgment when analytics outperforms it? was published on SAS Voices by Charlie Chase

11月 202017
 

Just last week, Walmart announced that they'll be testing inventory management robots. These robots will cruise store aisles, scanning shelves to identify out-of-stock products and other issues. According Reuters, Walmart is testing these camera-equipped robots in a handful of stores, but plans to expand the test to 50 stores. We [...]

Effective retail planning requires precision and finesse was published on SAS Voices by Dan Mitchell

6月 272017
 

Let me start by posing a question: "Are you forecasting at the edge to anticipate what consumers want or need before they know it?"  Not just forecasting based on past demand behavior, but using real-time information as it is streaming in from connected devices on the Internet of Things (IoT). [...]

Forecasting at the edge for real-time demand execution was published on SAS Voices by Charlie Chase

5月 182017
 

Are you caught up in the machine learning forecasting frenzy? Is it reality or more hype?  There's been a lot of hype about using machine learning for forecasting. And rightfully so, given the advancements in data collection, storage, and processing along with technology improvements, such as super computers and more powerful [...]

Straight talk about forecasting and machine learning was published on SAS Voices by Charlie Chase

3月 312017
 

The U.S. Marshals Service is the federal agency known for bringing wanted fugitives to justice. Often, the Marshals Service gets attention for these arrests, but once the publicity has died down they face a basic challenge --- where to put the individuals in their custody. The agency uses data to [...]

U.S. Marshals Service use analytics to save more than $200 million was published on SAS Voices by Steve Bennett

10月 072016
 

Machine learning is taking a significant role in many big data initiatives today. Large retailers and consumer packaged goods (CPG) companies are using machine learning combined with predictive analytics to help them enhance consumer engagement and create more accurate demand forecasts as they expand into new sales channels like the […]

Machine learning changes the way we forecast in retail and CPG was published on SAS Voices.

5月 272016
 

"Correlation does not imply causation.” Does that bring back memories from your college statistics class? If you cringe when you hear those words, don’t worry. This phrase is still relevant today, but is now more approachable and easier to understand. Here at SAS, we use SAS® Visual Analytics to make […]

Correlations, forecasts, and making sense of it all with visualization was published on SAS Voices.

5月 142016
 

It was John Allen Paulos who said, “Data, data everywhere, but not a thought to think.” That rings true more than ever before. Companies are struggling with the deluge of data coming at them from multiple channels. But traditional data channels are just the beginning. Companies also are facing an […]

Data, data everywhere… was published on SAS Voices.

12月 222015
 

Although the title of this blog posting has all the ingredients to attract the eyes of an analyst, the content is targeted for all personalities of a digital marketing organization. Before we jump into the marketing analytic use case regarding forecasting, scenario analysis, and goal-seeking  for digital analytics, let's spend some time on the magic of stories. As Tom Davenport stated in his fantastic article titled, Telling a Story with Data:

"The essence of analytical communication is describing the problem and the story behind it, the model, the data employed, and the relationships among the variables in the analysis. When the relationships among variables are identified, the meaning of the relationships should be interpreted, stated, and presented relevant to the problem. The clearer the results presentation, the more likely that the quantitative analysis will lead to decisions and actions—which are, after all, usually the point of doing the analysis in the first place."

While creative visionaries and data scientists are both tremendous organizational assets within a team, it is the alliance between these two segments that will push marketing forward. Although aspirational, this is a difficult challenge to overcome. Let me begin by sharing a bit of my story - one that began with a four year career start in graphic design and creative marketing communications, and then taking making a leap to the quantitative side of marketing. I've seen and listened to how DIFFERENT these two segments of the marketing world are, and now as a preacher for the potential of marketing analytics, one's ability to make analysis interpretable and approachable is critical.

Google recently published a nice article titled, Staffing Your Marketing Measurement Team: Why You Need Data Storytellers, and one takeaway that I love from this piece is:

"The true value of data emerges when marketers are able to use it to tell a meaningful story. Enter the data storyteller, or marketing measurement analyst. This is the person who can push the tools, translate insights across the business, and motivate stakeholders to participate."

This quote nails the crux of the issue - if we don't take ACTION on the insights of analytics, it was nothing but a school project. Influencing decision-makers within an organization isn't easy, and if they do not understand the analysis, nothing will ever change. There are people who are good at creative marketing strategy, and there are people who are good at marketing analytics. However, there aren't many people who can toggle between the two, and serve as the translator who inspires both sides.

In my personal opinion, the recent surge in analytic technologies becoming more approachable is key. The special ingredient in that trend is visualization and analytics joining forces in ways we have never seen before. Why is this happening? Seeing and understanding data is richer than creating a collection of queries, dashboards, and workbooks. According to the infamous American mathematician John W. Tukey:

"The greatest value of a picture is when it forces us to notice what we never expected to see.”

The "ah-ha" moment. The best part of my work day!

In addition, when analytics becomes approachable, interpretable, and transparent to the entire marketing organization, the behavioral change of how we work together highlighted in this video becomes a reality:

Visual Analytics represents a new category of interactive and collaborative technology to provide a path to be curious and innovative. Marketers are imaginative, and are constantly pushing to analyze new and exciting data sources (i.e. clickstream, social, IoT wearables, etc.), which require the ability to scale to very large amounts of information. However, what is different here is the ability to perform sophisticated analysis, and produce visualizations to support data-driven storytelling.

Finally, we arrive at the digital analytic use case. The intention is to highlight my personal approach to tip-toeing that fine line of producing meaningful analysis, while narrating the marketing storyline. Here is the description of the business case, and my demonstration video.

Business Challenge:

How do I allocate digital media spend to drive more traffic to my website in a future time period?

Marketing Applications:

  1. Identify the most important acquisition channels (i.e. attribution)
  2. Simulate & optimize ad spend to acquire incremental traffic and meet business objective

Let me know what you think in the comments section below. If you enjoyed this article, be sure to check out my other work here. Lastly, if you would like to connect on social media, link with me on Twitter or LinkedIn.

tags: data visualization, Digital Analytics, Digital Intelligence, digital marketing, Forecasting, Goal-seeking, marketing analytics, predictive analytics, Predictive Marketing, Scenario Analysis, visual analytics, visual statistics, web analytics

Forecasting, goal-seeking, and magical stories for digital analytics was published on Customer Analytics.