Digital marketing today

"There is one difference between winners and losers when it comes to web analytics. Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. Losers don't." - Avinash Kaushik in his blog post.

If you have read any blog post here you will notice that it’s related to digital analytics or web analytics. And, all of which tie up with digital marketing, which is where the sum of efforts you put into digital analytics (DA) is headed, in making your digital marketing better.

But, what is digital marketing anyway?

Source

Digital marketing is selling things to people via anything that is electronic, has a pretty screen and will let people click on it. Here's a definition from Wikipedia that leaves no doubts:

"Digital marketing is marketing that makes use of electronic devices (computers) such as personal computers, smartphones, cellphones, tablets and game consoles to engage with stakeholders. Digital marketing applies technologies or platforms such as websites, e-mail, apps (classic and mobile) and social networks. Many organisations cross traditional and digital marketing channels."

Today, when you talk about digital marketing you will hear words like Analytics, Customer Relationship Management (CRM), Visitors, Views, Engagement and what not. Digital Marketing is not what it once was in the 1990’s. Looking back, it has come a long way since.

Digital marketing centers around creating an experience for your customer, be it via Online, mobile or within social networks. It involves listening to how your customers interact with your digital content. Then, monitoring, predicting, experimenting and adapting what you deliver to what your customers want.

At this point, it's worth musing what Seth once said about connections in the digital age:

"There is no market for humming, for example, because everyone has unlimited humming at their disposal at all times. So, in the abundant digital world, what's scarce? Where is the economy?

It's in connection.

Who trusts you? Who wants to hear from you? Who will collaborate and support and engage with you? 

These are things that don't scale to infinity. These are precious resources."

By knowing who your customer is, what he does and a whole lot of other details that have sparked off the privacy debate, you can make your marketing more relevant and experience more personalized. (You've surely read this one, I presume.)

Almost everything digital that touches your customer, can be used to make his or her experience wholesome. Like, altering your landing page based on feedback from your digital metrics. And, with the state to which social media has evolved to what it is today, and data driven decisions it is possible to reach out to your customers at a personal level than ever before. It possible to connect with your customer than ever before.

Previously, what was once traditional marketing, today works in tandem alongside digital. Here’s an example of how that could be done:

“Each year companies spend millions of dollars for a 30-second Super Bowl ad to reach a wide and captive audience. By adding a digital call to action--like an invitation to like the brand’s Facebook page to be entered in a giveaway--brands can extend the value of that advertisement and get a broader return on their (very significant) investment. Once that consumer engages online, marketers can provide additional details about the product in the ad, invite them to opt-in for future communication, or offer a digital coupon or promotion in order to encourage the type of active engagement that digital channels have to offer.”

Here are few relevant numbers that show the state of things these days:

• Internet users: More than 36% of the global population today, compared to 21.7% in 2008.

• Mobile phone users: 60.7% of the population this year, compared to 40.0% in 2008.

• Smartphone users: Just under one-third of mobile users and about 20% of the global population, compared to 3.7% of mobile users and 1.5% of the population in 2008.

• Social network users: About a quarter of the global population, compared to 8.3% in 2008.

• Facebook users: More than 15% of the global population, compared to 3.1% in 2008.

• Total ad spending: $517.10 billion in 2013, up 2.8% from last year, compared to $484.30 billion in 2008.
  
• Digital ad spending: More than 22% of total ad spending in 2013, compared to 12% in 2008.

• Mobile ad spending: Just 2.6% of total ad spending and 11.9% of digital ad spending, compared to 2.1% in 2008.

And to close, here's an infographic from Mobile marketing watch relating analytics and digital marketing:

Source

References:

1. Digital Marketing and measurement model 

2. Digital Marketing

3. The end of the expert - why no one in marketing knows what they're doing

4. Making digital and traditional marketing work together

5. Worldwide Ad Growth Buoyed by Digital, Mobile Adoption

6. Seth's Blog: Scarcity and abundance in the digital age

7. Infographic: Analytics Driving Digital Marketing

Total Experience Design – A New Model for Customer Experience

How does one create a great customer experience for their customers? What are the secrets of obtaining customers and keep them coming back? These are the questions that anyone that is involved with a business asks themselves, but may not be able to answer. Recently Al Nevarez from Allegiance recently visited the Web Analytics class at the University of Utah to provide insights on how to answer these questions.

What kind of company is Allegiance and what do they do?

According to Allegiance’s website, “Allegiance was formed in 2005 when SilentWhistle, an ethics compliance company founded by Adam Edmunds, merged with Allegiance Technologies, a provider of web-based feedback tools founded by Dr. Gary Rhoads. Since then, Allegiance has grown to become one of the leading providers of Enterprise Feedback Management solutions. In July 2009, Allegiance acquired Inquisite, an innovative provider of online survey software based in Austin, Texas.”

Allegiance also provides a company overview and describes their services, “The Allegiance Engage platform is a feedback system that continually collects and analyzes the voice of customers and employees. Engage has the unique capacity to collect feedback through multiple channels (email, Web, print, phone) and accumulate those responses in a central database for analysis and action.

The Engage technology platform encompasses a family of feedback solutions including customer loyalty and employee retention; we round out our service offerings with professional services, training and support. Allegiance experts help companies to select the best feedback channels, customize surveys, and execute a strategic action plan to yield measurable results.

Background on the ebook “Delivering Customer Intelligence”.

“Delivering Customer Intelligence” is an ebook compiled by Allegiance where industry experts share their own insight and experience in helping companies create a voice of the customer program. The book can be downloaded by accessing Allegiance’s website here. The book discusses topics such as the economic benefit of listening to customers, how to approach the customer experience, creating measurable outcomes, and gives several case studies of companies that have used the tools discussed in the book.

What is the Total Experience Design?

According to Al Nevarez, The Total Experience Design integrates functional, activity, and life needs with the right mix of basic, performance, and delight features. He writes that the “Total Experience Design model provides a simple yet comprehensive means of auditing your customer’s entire experience”. In the book “Delivering Customer Intelligence”, Al Nevarez suggests nine possible areas to analyze when addressing the experience of customers. He provides the following visual to better explain the Total Experience design:

http://www.allegiance.com/blog/designing-a-great-customer-experience-strategy/4143

        

You will notice that this model addresses the features that a customer is looking for. These features are noted as the basic features one expects from a service or product. Performance features considers any additional benefit above a basic feature, and delight feature looks at those characteristics that a customer would not necessarily expect in a product but enjoy having them. These features are then compared to the different types of needs such as Life, Activity, and Functional needs.

How would a company come to know what their customer’s needs are and what features to provide to their customers to fulfill these needs? Mr. Nevarez suggests a variety of different methods, but focuses on four key items. These include Design Thinking, Observing Customers in Another Industry, See Products as Verbs, and Buy Your Customers a Gift.

-Design Thinking is an approach to finding great ideas that focuses on five steps. These steps include Empathize > Define Problems & Opportunities > Brainstorm > Prototype > Test.

-Observing Customer in Another Industry suggests that Life Needs and Activity Needs are common to many people, that they can be identified in any industry. He says to always be listening to people no matter what the product is.

-See Products as Verbs helps one see any issues or opportunities that have not already been identified.

-Buy Your Customer a Gift encourages a company to listen and get to know their customers so that they may be comfortable in purchasing a gift that their customers would like. This requires a company to listen and truly know who their customer is.

As it becomes ever more competitive to attract and retain customers, it is imperative that we understand the needs and wants of these customers. Please visit www.allegiance.com for more advice on building a customer intelligence program.

Sources:

http://www.allegiance.com/

Peppers, Don & Rogers, Martha. “Delivering Customer Intelligence” Allegiance 2012

In-Store Analytics - Bringing Digital Analytics to Brick and Mortar

In-Store Analytics

Bringing Digital Analytics to Brick and Mortar

Gordon Oremland

     There is no arguing that digital analytics helps a business maximize the performance (by whatever criteria they choose to measure this) of their online presence. But what are businesses supposed to do about their retail settings? Well, the answer to that is simple (or seemingly so): Digitize it!

      Simply put, the behavior of customers in retail stores can be viewed as being very similar to the behavior of visitors. They arrive, they may leave, they may wander and browse, they may view a particular item, compare it to another, etc. In the end, they either proceed to the check-out with their shopping cart or abandon it. See, even the terms used are the same! We need to find a way to track a physical customer's activity in a store to apply some useful analysis. Unfortunately, the usual three exit questions are insufficient:

• Did you find everything you were looking for today?
• How did you hear about us?
• Would you mind filling out a brief online survey in exchange for a $X.XX savings on your next visit?

These are all helpful and useful, but they don't offer the depth that current digital analytics provide in the online world. Enter the realm of In-Store Analytics!


     Online Digital analytics offer information such as where someone clicked, how much time they spent, where it was spent it and then what purchases were made.

     So ... how do they do it? There are several technologies at play here. I will discuss a few of these.
     Just a few companies with solutions in this area are:

• Path Intelligence
• RetailNext
• Nearby Systems
• Ekahau
• Shopperception
• Euclid

     These companies offer a mix of different tracking modalities, some of these will be discussed here.

     Video: a series of cameras located around the store and connected to the monitoring system. When a customer enters, they are scanned and registered on the system along with their entry time facial recognition software can give them a unique identification to follow as they work their way around the store (as a side note, this information can be stored to track return visits). The system can then track their whole behavior throughout the retail visit. The system can track where you walked, where you lingered, WHERE YOU LOOKED! If a shopper comes in and leaves without lingering anywhere - BOUNCE. If a customer fills a cart then leaves it - CART ABANDON. If a customer leaves with an item not paid for - SHOPLIFTING!!!(ok not a parallel to online, but useful in loss prevention - remember the facial registration?). When a person checks out, they may provide personal information. This can be linked to their facial identity. With this information combined with their purchases, the areas they browsed, their email address (if provided), previous purchases, membership in a loyalty club, etc. Can be used to customize offers and content than can be served to them via a variety of channels.

     RFID tags: Another way to visualize consumer motion and behavior around a retail space would be to use a series of sensors and RFID tags. With sensors placed throughout the retail space, RFID tags can be placed on shopping carts, baskets, merchandise tags, etc. By tracking the motion of these tags around the store, much of the same data than could be retrieved from the video option can be gleaned as well. Timing on a cart or basket begins with the removal of the cart from the corral. Timing ends with return to corral or with proximity to checkout. The time spent lingering at any given place can be recorded and logged for analysis or even real-time viewing. If an even greater depth of information is desired, a sensor can even be placed on the cart. This way, the system could even track what items were placed in or discarded from the cart. This can be very telling if an item is discarded and replaced with another similar one (for re-shelving purposes, it can even tell clerks where a removed item was left). If it is a store with a customer loyalty program, the loyalty card can be tagged with an RFID device now allowing specific tracking of identified customers. Again with this information, specific customized deals and information can be served to the customer later.

     The most intriguing, in my opinion, of the technologies is that of Smartphone Tracking. As has been discussed widely elsewhere in this blog, the sheer number and prevalence is staggering. More importantly, most of these devices are WiFi enabled. Most of the phone holders have limited data plans and so use WiFi at home or whenever they can. Most of us don't turn off our WiFi capability when we leave home. Therefore many people entering a retail establishment have a personal WiFi device in the "on" mode in their possession. What many people don't realize is that these devices send out a periodic "ping" looking for nearby WiFi. This ping contains some information including the device's MAC address. This can be detected and, with the right sensors, tracked. This tracking is accomplished with sensors attached to the store's network and placed in various areas around the store. This even allows behavior outside the store to be tracked! A retailer can see how effective their window display is at attracting customers. Since the ping is automatic there is no opt-in or out issue. On the other hand, if the store provides a free WiFi service in the store, even more personal information can be linked. If
the user logs in with their customer loyalty account?!?! You get the idea.

     So, what's the big deal? These systems turn a physical Brick & Mortar retail space into a digitally active analog for a web site. Now that that is done, the motivations and actions are the same as in the online world. The goal remains to get people into the store (site) view your merchandise (view pages and content) and make purchases(conversions). This is the case at least in retail although other brick & mortar settings can make use of this as well. They just need different conversions. A few examples would include a library, a medical setting, a conference, etc. For now, I'll only address commercial instances.

Eye Tracking

     One of the things site administrators are trying to achieve through analytics is to determine where people are looking on their site - literally - where they are looking. using eye tracking, the places an eye looks, tracks to and lingers can be mapped. This helps give insights as to what display content is effective. The site can then be adjusted to maximize effectiveness. This is easily applied to a store. With the previously discussed technology, you can readily track location and location density in store. Furthermore, depending on the technology, you can track which lingers led to which purchases. Another specific example of this utility is best illustrated with the following scenario:

In-Store Tracking Heat Map

     Imagine a popular retail electronics chain. For the sake of argument let's call it Superlative Purchase. They have several large live game console displays near the game consoles for sale. People can come over and play on them. These displays use up a fair amount of maintenance, display real estate and to a small extent power. These systems can track the amount of time people (and potentially specific people) spend on the console and determine whether or not this playtime led to a purchase. If it leads to purchases, then keep it. If no purchases happen from this feature, the space could be shifted to more productive use.

     This, of course is not the only use of these analytic tools. They can be used for all of the purposes and with most of the measures that online provides. in some cases more. If there is an area in the store of chronic bottleneck, this can be mitigates. With the use of real-time heat mapping, if there is a temporary bottleneck, it can be addressed immediately. There are a couple of exceptions. There is a great deal of information in online analytics. For example, there is geographical information with website visits. This is not necessarily the case in-store unless the shopper fills out a loyalty membership form or is already a member. On the other hand, in all likelihood, in store visits are from local customers. Another lacking measure is that of referring site. This, however, can be mitigated by the second question at the beginning of this article. Furthermore, there are several measurements of referral sources that can be integrated from various nonline sources such as offer codes, coupons, etc.

     In conclusion, it is clear that there are many benefits of being able to leverage web analytics. Now, with the addition of some technology, physical stores can apply some of the same powerful analytics to obtain insights to improve their businesses. They can even be beneficial to stores without an online presence. On the other hand, with an online store as well, the information can be combined, integrated and information can be served to improve conversions and customer experience even more. A few different technologies have been discussed. No one technology alone will provide as deep a set of data as a combination of them. In fact the above listed companies all use a mix of these (and other) technologies.

References:

http://www.retailnext.net/ 

Not covered in this article, but interesting:
http://chainstoreage.com/article/using-store-analytics-combat-showrooming

http://euclidanalytics.com/product/how/

http://phys.org/news/2011-11-google-analytics-inventor-concept-physical.html

http://shoppersciences.net/in-store-analytics/

http://postscapes.com/in-store-analytics

Data can help us, even outside the web

DATA CAN HELP US, EVEN OUTSIDE OF THE WEB

Today, nearly every dimension of personal and professional life will produce, interact, and sometimes be drowned by data. With the ever-increasing amount of digital devices at hand, huge stores of data are now automatically recorded, providing detailed code-bits of information that can illustrate at fundamental levels the complex array of activity people engage with every day. This information is hugely valuable, yet our cognitive minds are poor at deciphering data to recognize relevant patterns that can provide insight to improving our activities. The use of customer analytics and data mining processes can provide insight into how customer behavior is affected by particular sets of decisions. Data mining is a process that extracts previously unknown, interesting, valid, and actionable data patterns from a large set of data for supporting decisions and providing Business Intelligence (BI). This data can be analyzed to make key decisions in customer behavior, site selection, customer relationship management, and even something apparently unrelated such as physical retail design. But how can customer analytics and digital data translate into a physical world and aid us in something such as a retail store design? In order to do so we much first understand what problem we are trying to solve and identify what data can augment our understanding of a particular business scenario. What we find is that the way in which a scenario plays out is often different than the subjective observations we make.

            Most retail stores use a basic principle of association patterns to locate items of relationship in close proximity to each other in order for the customer to identify related items that they will likely also purchase. For example, furniture shopping is largely a contextual experience. That is, one envisions the environment that a piece will fit into and shop based upon not only the piece itself, but how it complements other pieces in a setting. For this reason, the purchase of furniture will often lead to the purchasing of other pieces that go in a set. An obvious example is the purchase of a bed; customers will often consider case pieces such as dressers, nightstands, and armoires. Therefore, strategic settings of furniture provide customers with examples of complementary items that can provide them with a vision of how a room will look and feel (this envisioning is often difficult for customers to do themselves). Using insights from data mining, we can apply the principles of association patterns analysis to determine which items were often purchased together, and provide insight into the most advantageous methods for store layout.

            But how can customer analytics help in this arrangement? Many companies that specialize in luxury goods maintain a robust historical database of computerized customer account information (such as a SQL software application). For companies even operating outside of the web, this data can provide us with the first preliminary steps in our analysis. For the furniture retail store, data can still provide insight into furniture categories (bedroom, office, kitchen, etc.). By mining the data for association patters, we can determine the most frequently purchased items that occur with individual customers. This will have to be evaluated over time as people rarely purchase all their home furniture in one transaction. Therefore, queries into the data should the customer accounts within certain time frames (3-12 months). This will yield scenarios that are more likely a result of customers experience on the retail floor rather than situations where customers returned a year or more later to purchase an unrelated item. By analyzing the correlation among pieces purchased, the company can utilize the patterns that show high-correlation to improve the design of the store layout. By repeated analysis, the company can analyze the effectiveness of a particular layout and refine their strategies to locate more and different patterns.

            This is only one dimension that customer analytics can be enhanced by data mining processes. But the analysis should reveal how effective data can be in providing an objective window into patters of customer behavior if the right questions are asked and the right data acquired.

Sources:

http://www.forteconsultancy.com/content/detail.aspx?cid=24&ngId=6&cntid=179&scid=52

Eric Siegel, Predictive Analytics with Data Mining:
How It Works, 2005