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Machine Learning Marketing: How to Improve Your Customer Experience
If you are entrepreneurial in nature owning a business is very exciting adventure. It can also be the most difficult thing for you to get into if you are not prepared.
Hollywood paints a grim picture of a future populated by intelligent machines. Terminator; A Space Odyssey, The Matrix and countless other films show us that machines are angry, they’re evil and, if given the opportunity, they will not hesitate to overthrow the human race. Films like these serve as cautionary tales about what could happen if machines gain consciousness (or some semblance of). But in order for that to happen humans need to teach machines to think for themselves. This may sound like science fiction but it’s an actual discipline known as machine learning.
Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.
For digital marketers, machine learning may be especially helpful in getting products or services in front of the right prospects, rather than blanket-marketing to everyone and adding to the constant noise that is modern advertising. Machine learning will also be key to predicting customer churn and attribution: two thorns in many digital marketers’ sides.
Despite machine learning’s positive impact on the digital marketing field, there are questions about job security and ethics that cannot be swept under the rug. Will marketing become so automated that professional marketers become obsolete? Is there potential for machine learning systems to do harm, whether by targeting vulnerable prospects or manipulating people’s emotions?
These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.
What is Machine Learning?
You can think of machine learning as using a computer or mathematics to make predictions or see patterns in data. At the end of the day, you’re really just trying to either predict something or see patterns, and then you’re just using the fact that a computer is really fast at calculating.
You may not know it, but you likely interact with machine learning systems on a daily basis. Have you ever been sucked into a Netflix wormhole prompted by recommended titles? Or used Facebook’s facial recognition tool when uploading and tagging an image? These are both examples of machine learning in action. They use the data you input (by rating shows, tagging friends, etc.) to produce better and more accurate suggestions over time.
Other examples of machine learning include spell check, spam filtering even internet dating - yes, machine learning has made its way into the love lives of many, matching up singles using complicated algorithms that take into consideration personality traits and interests.
How Machine Learning Works?
While it may seem like witchcraft to the layperson, running in the background of every machine learning system we encounter is a human-built machine that would have gone through countless iterations to develop.
Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.
So how exactly does machine learning work? Spoiler alert: it’s complicated. So without going into too much detail, here’s an introduction to machine learning, starting with the two basic techniques.
Supervised learning systems rely upon humans to label the incoming data - at least to begin with - in order for the systems to better predict how to classify future input data. Gmail’s spam filter is a great example of this. When you label incoming mail as either spam or not spam, you’re not only cleaning up your inbox, you’re also training Gmail’s filter (a machine learning system) to identify what you consider to be spam (or not spam) in the future.
According to Tommy, this type of machine learning can be likened to the relationship between a parent and a young child. When a child does something positive they’re rewarded. Likewise, when “[a machine] gets it right - like it makes a good prediction - you kind of give it a little pat on the back and you say good job.”Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.
Unsupervised learning systems use unlabeled incoming data, which is then organized into clusters based on similarities and differences in the data. Whereas supervised learning relies upon environmental feedback, unsupervised learning has no environmental feedback.
The Power of Machine Learning
A lot of what machine learning can do is yet to be explored, but the main benefit is its ability to wade through and sort data far more quickly and efficiently than any human could, no matter how clever. Tommy is currently experimenting with an unsupervised learning system that clusters landing pages with similar features. Whereas one person could go through a few hundred pages in a day, this model can run through 300,000 pages in 20 minutes.
Machine Learning and the Digital Marketer
As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data. This process usually involves hours of digging through analytics, collecting data points from marketing campaigns that span several months. And while focusing on data analysis and post-mortems is incredibly valuable, doing so takes a significant amount of time and resources away from future marketing initiatives.
As advancements in technology scale exponentially, the divide between teams that do and those that don’t will become more apparent. Those that don’t evolve will stumble and those that embrace data will grow — this is where machine learning can help.
That being said, machine learning isn’t something digital marketers can implement themselves after reading a quick tutorial. It’s more comparable to having a Ferrari in your driveway when you don’t know how to drive standard or maybe you can’t even drive at all.
Until the day when implementing a machine learning system is just a YouTube video away, digital marketers could benefit from keeping a close eye on the companies that are incorporating machine learning into their products, and assessing whether they can help with their department’s pain points. So how are marketers currently implementing machine learning to make decisions based on data rather than gut instinct? There are many many new niches in marketing that are becoming more automated.
Is Predictive Intelligence the Frontier of B2B Marketing?
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Marketing strategy is the primary key to business success. The No. 1 reason businesses fail is that they don't make enough money. And the No. 1 reason they don't make enough money is that they don't adequately understand and practice effective marketing strategy. Marketing strategy offers these powerful benefits:
- Concentrating your resources and efforts on your greatest opportunities for success
- Sharpening your competitive advantage so that your business is superior to your competitors' in ways that matter to customers
- Increasing the income of the firm more effectively than any other way
- Uniting the leadership team to all pull in the same direction, maximizing positive results
- Giving your brand a clearer focus so that it will be better known in the marketplace
- Stimulating demand for your products and services
- Improving the effectiveness of messages you send to customers and prospects
- Strengthening your ability to understand and meet the needs of customers
- Ensuring that your business will survive and thrive far into the future
"Marketing strategy" is one of the top-10 search terms related to marketing, used by Internet searchers about a half-million times a month. Many people are obviously interested in learning more about marketing strategy. That's why this article has been written, the first in a series that explain marketing strategy in detail. The author, Buck Lawrimore, has provided marketing strategy to hundreds of business, government and nonprofit organizations of all sizes for more than 27 years.
Definitions of Marketing
"Marketing" comes from the Latin word merx or mercis meaning merchandise. Originally a market was a large open space where merchandise was displayed for sale, like pictures we've seen of large open marketplaces in Third World countries, or today's farmer's market. Originally "marketing" involved selling products in a marketplace. And that's still the core meaning. But professional marketing has evolved to such a high degree of sophistication, like computer science and medicine, that it involves much more than just selling in a marketplace.
The American Marketing Association, the largest professional organization of marketers in the U.S., defines marketing as follows:
"Marketing is an organizational function and a set of processes for creating, communicating and delivering value to customers and for managing customer relationships in ways that benefit the organization and its stakeholders."
This definition makes no mention of generating sales and income, the primary aims of business marketing, perhaps in deference to the many nonprofit organizations which are members of the AMA and are more focused on "delivering value" and "managing customer relationships."
Another way to understand marketing is to view it as a mindset or orientation of the business or organization. The so-called marketing orientation means the organization as a whole is oriented to understanding and meeting the needs of customers. A company with this orientation is market-driven. It focuses its strategy and operations on understanding and meeting the needs of customers in a manner which is superior to competitors. Procter & Gamble is one of the largest and most successful companies in America, and it has a strong marketing orientation. SAS Airlines, FedEx and other leading companies around the world have a passion for understanding and meeting the needs of customers. That's how they became so successful, and that's how your organization can become more successful than ever before, whether you aim to be a world leader or just the best in your neighborhood at what you do.
Definitions of Strategy
"Strategy" comes from the Greek word strategos meaning general. Strategy defined by Webster's as "1 The science of planning and conducting military campaigns on a broad scale." More recently strategy has come to mean "skill in management" or "an ingenious plan or method."
There are two aspects or connotations to this idea of strategy. The first is, it's big picture. It involves consideration of all your available resources - people, money, time, physical resources etc. "on a broad scale." The second is, strategy involves winning some form of competition. Your opponent may be an enemy who is trying to defeat you, or a business competitor who is trying to get your customers to buy from them instead of from you, or an opposing athletic team in a sports event. In all these situations as well as your own real world, there is one key to all effective strategy. This is one of the most important things for you to learn from this book:
The key to all effective strategy is
concentrating your resources on your greatest opportunities,
where your competition is weak.
Definition of Marketing Strategy
So then, effective marketing strategy could be summed up this way:
"Concentrating the organization's resources on its greatest opportunities
to better meet customer needs, outperform competitors, increase income,
and achieve enduring success."
Implied in this practical definition is the key idea that you have or will develop a niche or position in the marketplace which you can dominate or at least be a top player in, by building on strengths which distinguish you from your competition. Also implied is that you will be most successful if you concentrate on better meeting customer needs (via the marketing orientation) as a path to increasing sales, rather than just focusing on outbound communications or a sales force to persuade potential customers to buy.
Networking has always been considered a powerful tool for improving business prospects, advancing a career, and developing ideas. Other than some brief, structured events, networking has been mostly informal and inexpensive in comparison to cost they otherwise spend on different channels. But membership is growing in many formal, long-term networking groups, and so is the price tag.
Our groups are not groups for generating sales leads, nor are they places where individuals can drop-in to gain quick advice on an immediate challenge. Members also sign a confidentiality agreement and benefits from the guided mentoring to help each other.
These groups include an experienced facilitator and use a structured discussion method to ensure appropriate participation.