Monday, March 2, 2020

Definition of Digital Ecosystem

Gartner has a succinct definition:

A digital ecosystem [is] "an interdependent group of actors (enterprises, people, things) sharing standardized digital platforms to achieve a mutually beneficial purpose."

Related Links:
Managing ecosystems from McKinsey

Tuesday, November 28, 2017

How to Build a Successful Martech Stack

Marketing automation is not a subject specifically covered in the 4th edition, although there are discussions of specific automation tools like Email Management Systems. Social Media Marketing does have a chapter on tools because the sheer complexity of SMM requires some degree of automation.

In the same spirit, the term "stack" is occasionally used, perhaps with a graphic portraying one, but the concept of a software stack is not specifically discussed. The number of software tools available to marketers, and the growing importance of their use, suggests that an introduction to the concept of a marketing technology (martech) stack might be useful. Hence the infographic.

building a martech stack
                         Example 1                             Example 2                         Example 3 

CMO lists essential tools for a martech stack as being:
  • Content Management System
  • Customer Relationship Management
  • Email and Customer Nurture
  • Acquisition/Advertising
  • Optimization/SEO
  • Social Media Listening and Analytics.
That list misses two other essential components. First the tools that ensure that customer data is of the highest quality and that it paints a complete picture of the customer. Second, the operating system  and runtime environment (Java, for example) that executes the software and allows all the tools to work smoothly together. That's what makes it a "stack," not just the collection of tools that most marketers appear to have at the moment.

marketing technology landscape
2017 Marketing Technology Landscape
In order to understand both the complexity and necessity to build a custom stack that efficiently meets the needs of the business, view the 2017 marketing technology landscape graphic. Just looking at the structure, the six columns of marketing activities and the category headings within each of those, is helpful. Sorry, but you'll probably have to use the link to find a larger version before you can do even that!

Whether the business builds its own stack or whether it brings in an agency to assist, building a successful martech stack is not a "one size fits all" activity. It needs to be tailored to the business's priorities, long-term as well as short-term, and to the resources, both human and financial, it can devote to building and using the stack.

The examples links above are interesting and instructive, but again, this should not be a "choose one" project. Reading helpful content about building stacks would be a better use of time and the CMO link is a great place to start.

Sunday, November 19, 2017

How Intelligent Chatbots are Revolutionizing Marketing

When I was writing the first edition of Internet Marketing back in the internet bubble and burst days of 2000 – 2002, I was especially pleased to have added a customer service chapter to the standard marketing fare. That effort was full of discovery including “agent technology” at a firm called Artificial Life, which no longer seems to exist at least in the same format. The featured bot was Lucy McBot, who was able to speak to the user in several different languages. As I remember there were several bot personas and good demos on the website. Using them in the classroom was fun and one of the book’s adopters pointed out to me that Lucy was programmed with snarky answers if a caller asked for a date. And that is exactly my point. They used programed responses and since natural language understanding was well less developed, these early bots were limited in their ability to communicate.

By the third edition the virtual agents had dropped out in favor of other technology advancements like mobile apps and social media, although there is one brief mention of virtual assistants. That perspective continued into the current edition with focus on customer experience in multi-channel environments and the impact of social media on experience. There just didn’t seem to be exiting developments in the use chatbots in customer care.

HubSpot messaing timeline
HubSpot Messaging Timeline
Fast forward about two years from the time that chapter was being written and witness the explosion of the intelligent (AI-driven) chatbot. It is one aspect of the explosion in AI that is all around us and offering many opportunities to marketers. HubSpot traces the evolution of bots from those early days to the AI-driven bots of today.

How Marketers Are Using Chatbots

Marketers are continuing to improve customer service bots, especially by adding AI. One article indicates that there is an opportunity for US businesses to automate 30% more of their customer contacts and save over $23 billion in customer service costs. Bots, though, are now being used in many more marketing applications. Some examples are:

•    The Cosmopolitan Hotel in Las Vegas introduced a bot named Rose in January 2017. For visitors Rose fields texts to room service as well as texts that would otherwise be questions for a human concierge (a human is standing by in case Rose can’t answer the question). She is fond of snappy answers and emojis, as you can see from the conversation below.
Cosmopolitan Hotel chatbot
A Conversation with Rose at the Las Vegas Cosmopolitan Hotel
Rose also helps potential guests book their stay at the Cosmopolitan. The agency that designed Rose says that guests who booked on the Cosmopolitan site through Rose spent 39% more than guest who did not engage with the bot.

•    1-800-Flowers was already using Facebook Messenger. When Facebook added chatbots to Messenger in 2016 they were quick to create one. Later they added an IBM Watson-powered bot called Gwyn (Gifts When You Need) to their site. 1-800-Flowers says that over 70% of chatbot orders have come from new customers and those new customers are younger than its existing base

1-800-Flowers Messenger and downloadable chatbots

•    Sephora introduced its Kik messaging app with a Story on Snapchat to attract the teen segment of its audience. The app features a quiz that helps the bot understand the user’s makeup needs.
Sephora chatbot with quiz
Sephora Chatbot
Sephora already had two Facebook Messenger bots, a Reservation Assistant for booking facials and Virtual Assist to help in selecting makeup colors.

•    In 2016 the NBA launched a bot on Facebook Messenger so fans could chat about the NBA finals. The app asks the user to select the team, then whether she wants playoffs or game highlights. A highlights offering is shown below. Not to be outdone, the Golden State Warriors created a bot for the 2017 playoffs. The chatbots follow on the heels of the NBA mobile app discussed in Chapter 12.

NBA and Warriors Messenger chatbots

Notice that the chatbots are being used either for direct sales or for customer engagement. And especially notice that many of them are on messaging platforms, not the brand’s website. Why is that?

Bot Platforms

Why are so many chatbot apps being built on messaging platforms? HubSpot has a powerful answer:

bots solve the thing we loathed about apps in the first place. You don't have to download something you'll never use again. It's been said most people stick to five apps. Those holy grail spots? They're increasingly being claimed by messaging apps. Today, messaging apps have over 5 billion monthly active users, and for the first time, people are using them more than social networks.     

The statistics vary a bit, but there is agreement on which messaging platforms are the top three. These numbers are taken from Statista 2071 reports for consistency. Monthly active user for each platform are:

•    WhatsApp                         1.3 b   
•    Facebook Messenger       1.2 b       
•    WeChat                          963m

Other trending messaging platforms include Kik, LINE, Telegram and Kakaotalk.

The marketers in the examples above were already using messaging apps. Why take on the challenge of trying to create an audience for a downloaded app, especially when most are not used for long?

There many services in addition to the guidance provided on the platforms that will assist the technically-deficient marketer in building apps. Many offer free initial use.  Here are 3 lists and there are many more. 1  2  3

How Chatbots Can Boost Marketing Impact

As the examples show, intelligent chatbots have much to offer marketers. They can make it easy and fun to communicate with a brand, thus building engagement. In addition to making sales and enabling payments, they can help qualify leads. In addition:

•    They can send notifications.
•    They can collect feedback and generate insights.
•    They can offer personalized experiences.
•    They can give impetus to a content marketing strategy.

AI-driven chatbots have burst upon the scene and established themselves as an important factor in marketing with great rapidity. Marketers would be well advised to look for opportunities to increase their effectiveness with chatbots. As they do, they must remember that, in the end, customer experience is all important!

See infographic with additional data

Related Links 
Chatbot metrics
2018 chatbot trends 

Sunday, October 29, 2017

How the General Data Protection Regulation (GDPR) Will Impact U.S. Companies

GDPR website
The European Union’s 1995 Privacy Directive had strong protection for the privacy of personal data for EU residents and the movement of data across borders. The directive required all EU nations to establish their own laws under its framework. All companies with businesses that collect EU customer data, wherever they were headquartered, were covered by its provisions. The US and the EU established a Safe Harbor agreement to certify that US member companies were complying with EU regulations. The 1995 directive provided strong privacy regulation for many years but now that is changing.

What is the GDPR?

In 2016 the EU passed the GDPR with an effective date of May 2018. The regulation updates the existing procedures under the 1995 directive. Most important, it is a regulation with the force of law, not a directive that directs member companies to establish laws. Industry group Third Certainty (so named because observers believe that today’s third certainty after the traditional death and taxes is identity theft) describes the regulation as follows:

GDPR isn’t a suggestion that companies institute best practices for customer data privacy; it is a directive that could result in fines of €20 million or up to 4 percent of annual global turnover. Not only will all companies in the EU be required to meet the new regulations, but GDPR also is in effect for all organizations that hold or process the data of customers who live in the EU.

In addition, the GDPR site identifies major changes as:
•    The unambiguous inclusion of all companies that process the data of people residing in the EU no matter where the companies are located.
•    Consent to be obtained in a clear and accessible way, free of legalese, and the purpose for processing the data must be explained. It must be as easy to withdrawn consent as it is to give it.
•    Data breaches to be revealed within 72 hours of the company first being aware of the breach. Data processors are also required to notify of breaches without undue delay when they become aware of the breach.

According to the Information Commissioner’s Office in the UK the rights of individual data subjects are:
•    Right to be informed by means of privacy notices
•    Right of access to their data a
nd information about how it is being processed
•    Right to rectification of inaccurate or incomplete data
•    Right to erasure of data where there is no compelling reason for continued processing
•    Right to restrict processing of personal data
•    Right to data portability, allowing subjects to move, copy or transfer personal data easily from one IT environment to another.
•    Right to object to certain types of processing
•    Rights related to automated decision making and profiling that protect against potentially damaging decisions made without human intervention.
notice that cookies are being collected
Cookie Notice from

The ICO Guide has more detail on these provisions and a “What’s New” page that highlights ongoing analysis. Notice that this information is being provided for UK organizations post Brexit on a site that has one type of cookie notification. The home page of the Financial Times shows another type of notification that is being used under the provisions of the regulation. Notice that this is the U.S. version of the London-based publication that is showing the same notification that is shown on the U.K. and World editions.
notice that cookies are collected
 Cookies Notice from
The individual rights under GDPR are based on the Fair Information Practices Principles discussed in Chapter 17. These specific rights update the 1995 directive by being clearer and more specific.

How Should U.S. Companies Prepare for the GDPR?

It seems the question should really be, “Are U.S. companies preparing for the GDPR?” A study by NTT Security, quoted by Thompson Reuters, found that many decision makers around the world were unaware of the regulation and how it would affect them. Switzerland had the highest preparedness level at 58% of businesses. The U.S. had the lowest level of awareness of the regulation with only 25% of companies believing the regulation would affect them.

The Thompson Reuters post says that the regulation:

attaches to any data concerning an individual residing or present in the EU. Thus, if data is connected to an individual in the EU, the GDPR applies — regardless of where such data is processed. They add that it requires that, “organizations be able to justify their reasons for holding or processing every piece of data in their possession."

Those are sweeping statements, especially in view of the large fines that can result from non-compliance. Steps that U.S. firms should take to comply are outlined by Information Week:

•    Determine whether the firm is a controller, a processor or both. A controller is the entity that determines the purposes and conditions under which personal data will be processed. Since processing includes anything as basic as collecting and storing data, that means that any brand that collects personal data is a controller. That definition is the same as under the 1995 directive. The definition of a processor also does not change; a processor is an entity that processes personal data for a controller. Both controller and processor(s) are responsible for compliance with the GDPR but primary responsibility lies with the controller

•    Audit personal data to ensure that there is a single view of each data subject. This is necessary to be able to “forget” a data subject under the regulation.

This can be a huge task, but Steve Forde of Britain’s ITV advocates viewing it as an opportunity. He finds 3 principles of data collection—transparency, control and value exchange—to be essential in creating trust with customers. Preparing for GDPR is a way to instill this philosophy throughout the organization with the result that customer trust should increase.

•    Redesign what consent looks like for your customers. They must explicitly consent to each use of their data and pre-checked boxes or opt-out requirements are not adequate. The range of data covered and special issues like collecting data from children have been make tighter and more explicit under the regulation.

•    Audit service providers to ensure they meet the requirements for processors. Otherwise the processing they do for a U.S. firm on its data for European subjects will be illegal.

•    There are other requirements like choosing a member state as the supervisory authority, appointing a data protection officer and locating data centers that are legal or technical in nature, but marketers need to be sure that all requirements are being met. Failure to do so could result in loss of access to data of European subjects—everything from contact information to CRM data. For many U.S. brands, that could result in a significant loss of business.

What is the Role of Privacy Shield?

privacy shield image
Privacy Shield prototype
Under the 1995 directive, the Safe Harbor program certified that U.S. companies were compliant with its provisions. That compliance framework has been superseded by the Privacy Shield program. Developed by the Department of Commerce, the service is open to all organizations that are under the jurisdiction of the FTC or the DOT. The framework allows companies to self-certify that they have met the requirements of the GDPR for both the E.U. and the separate Swiss framework.

Companies that wish to certify must have a Privacy Policy that is compliant with the GDPR. Current privacy policies will not conform to the new requirements, which are essentially the rights of individual data subjects listed above. The company must provide an independent recourse mechanism from an approved list that includes agencies like the Better Business Bureau and TRUSTe. The company must provide for verification of its compliance and designate a contact for the Privacy Shield program. Companies that certify under the Privacy Shield program will automatically be removed from Safe Harbor and must remove all references to it from their privacy policy and website.

U.S. Companies Should Move Quickly to Comply with the GDPR.

If this all sounds like a great deal of work, it is. At the same time, remember the advice of Steve Forde from ITV. Trust is essential to ecommerce businesses and being transparent about the way a brand handles the personal data of its customers helps create that trust.

So the best advice to U.S. companies is to move quickly so they do not lose access to the data of their E.U. customers and to do so in a way that creates trust with their customers all over the world.

See the infographic here 

Related Posts

Post-cookie (also called zero data) advertising 

Monday, October 9, 2017

How Image Search is Changing Shopping

Since Google Image Search was introduced in 2001 many of us have found it useful in a variety of ways. According to Wikipedia image search results are based on the file name of the image, the link text pointing to the image, and the text adjacent to the image. If you use the Google Images search box, you can drag and drop an image to search and that is kind of fun. Other search engines also offer image search but this post will focus on the impact of image recognition on shopping and how we are getting there.

What is Deep Learning? How is it Affecting Marketing?

Talking about AI-driven advances in image search immediately brings us to the subject of deep learning. Its development is explained in the Nvidia blog as

                       Artificial Intelligence  >>  Machine Learning >>  Deep Learning

Deep Learning layers for dog
Deep Learning Layers

The post explains that what we can do at present falls into the  category of “narrow (specific) AI”. Examples include image classification on Pinterest and facial recognition on Facebook. Machine learning uses massive neural networks, running huge amounts of data through a network until it learns to recognize the item with near perfection. The “layers” shown in the dog recognition graphic are at the heart of deep learning. Speech recognition and image recognition are both products of deep learning technology. The impact of voice technology was discussed in my recent post on voice search. Image recognition is, of course, the enabler of image search.

Image search is interesting in a general sense, but the recent presentation I developed on Social Commerce opened my eyes to some of the ways image search—fueled by AI—could offer new shopping opportunities. That presentation focused on Pinterest, clearly a leader in the social shopping space, and on Facebook whose sheer size makes it impossible to overlook its initiatives in social commerce.

The clear leaders in the image search space are, not surprisingly, the leaders in voice technology—Amazon, Apple, Google and Microsoft. You could probably add Chinese web services firm Baidu to that list, but less is known about the current status of its AI.

Amazon has been in the space for a considerable time, using images as one input in its recommendation engine. Over time, it has added AI/deep learning to its use of images. Amazon recently made news when it opened its deep learning framework DSSTNY to other developers as an open source platform. There was speculation in the trade that Amazon was using this as one way to catch up with the technology of its more recent rivals, especially Google. Facebook also has made its facial recognition software open source. Facebook’s facial recognition services have been a special target for privacy advocates, a subject in itself. Apple is using facial recognition to unlock the iPhone X.

Google is making advances in deep learning AI research on several fronts. In 2011 it introduced Rank Brain (discussed in Chapter 10) as part of its search process. At present, it also uses deep learning in a number of ways:

•    To help categorize images on the web to improve search results. It also allows image enhancement, essentially filling in the blank, when images are missing detail.
•    Google Cloud Video Intelligence allows videos to be segmented and analyzed for content and context with automated summaries provided. It can be used to search for various types of meaning including suspicious content. See a video demo on YouTube.
•    Language recognition technology is essential to Google’s growing line of home assistant devices.
•    Google also uses deep learning to improve recommendations on YouTube, thereby keeping users on the site longer.
•    It is enhancing Google Image Search with Pinterest-like suggestions about related content. For instance, it will highlight when a recipe is available for a particular food image.

Remember—it’s still early days for these technologies. Nevertheless, there are already useful commercial applications. The fashion industry with all its visual content provides some good examples.

How Image Search is Changing Fashion Shopping

Tech CEO Ron Palmeri says the smart phone camera is on its way to becoming “the keyboard” because it can capture so much more information than words alone. Palmeri said he imagines a time when a shopper takes a picture of a desired item and rather than typing in a keyword to find it, they upload the image to a search engine that spits back a number of similar items at a range of price points or even items customized to a specific price point, if the user has integrated financial data into the model.

Palmeri’s firm, Layer, supplies the search technology for Nordstrom’s Trunk Club. The Twitter box describes the service and a posting shows one offer. The postings tend to show accessorized outfits, but a customized tux was the most recent post when I visited. Note that a personal fashion advisor is available on the mobile apps. Trunk Club actually started in 2009 as a service for men who didn’t like to shop but its expansion to women’s fashion and the importance of the smart phone camera is putting the emphasis on mobile.

Trunk Club Offr
Trunk Club Twitter Offer

 Trunk Club Twitter Page

It’s about more than just selling; the importance of the images is influencing design at Nordstrom. “We are trying to understand how one pair of jeans plays out against another pair that was released in another season,” explained Justin Hughes, vp of product development and design at Trunk Club. “We want to get really granular and understand what really works.”

In a related development, Nordstrom is rolling out a line of stores with no inventory. The first store in Los Angeles has no merchandise, but it offers a fascinating array of services. See this post for a picture gallery that would stimulate a lively discussion about the future of retailing in the digital age.

British fashion supplier Apsos finds 80% of its UK traffic coming from mobile and 70% of its orders. Customers average 80 minutes each month on their mobile apps. No wonder Apsos is adding image search to its mobile apps! A customer takes a picture of an item or pulls one in from, say, Instagram for the search. The app returns similar items with reasonable accuracy, according to one reviewer. The results that don’t match so well may actually give customers more shopping ideas she says. There is plenty of room for ideation; Apsos currently has about 85,000 items in its image database.

the Find it on eBay demo
  Play the demo
We've all probably spent time searching for an item among the multitude available on eBay. Well, eBay will soon have an app for that! The app will allow the user to search not only for products but also for specific features of the product. The user can also choose the color. Play the description from the link in the caption.

Target has taken another route. The retailer is adding Pinterest’s Lens search technology discussed in the Social Commerce presentation) to its mobile app. Users take a picture with their smart phone and the search will find similar items for sale at Target. “The Pinterest partnership quite literally helps us shorten the distance from when our guests have an idea to when they’re ready to make a purchase,” said Rick Gomez, Chief Marketing Officer for Target. He adds that this technology will help understand what customers are looking for and therefore improve their merchandise planning.

What is the Future of Image Search?

There are a number of implications to be drawn from this discussion. As far shopping is concerned, many other visually-oriented categories like food should quickly be active in the space. The technology will continue to grow more powerful because of the players discussed here and other powerful ones, IBM for example, whose activities in deep learning were not discussed.

Brands have choices in terms of how to become a player in image-based shopping. Some will make a quick entry by partnering with a technology firm—Target and Pinterest, for example. Others will carefully build their own back-end processes, Apsos and eBay for example. Burberry is said to have engaged in massive image creation for a trial on Pinterest when it introduced its new Cat Lashes mascara. These activities are already beginning to impact the physical retail space as Nordstrom's new store illustrates.

Finally, search marketers will be pardoned if they emit another long sigh. Image search looks to be another disruptive development in the search space.

Look for all sorts of fascinating developments in the months and years to come!

Related Links

 AI that trains itself