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Why SEO & Machine Learning Are Joining Forces

The global datasphere will grow from 33 zettabytes (each equal to a trillion gigabytes) in 2018 to 175 ZB by 2025.

In marketing, our role as the stewards of much of this data is growing, as well.

As of last year, more data is being stored in the enterprise core than in all the world’s existing endpoints, according to a report by IDC.

The great challenge for marketers and SEO professionals is activating and using that data.

In 2025, each connected person will have at least one data interaction every 18 seconds and nearly 30% of the world’s data will need real-time processing.

There’s no way human marketers can handle this processing on our own.

And more and more, as our machine-learning-enabled tools process and analyze search data, they’re learning and improving their understanding of it as they go.

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Machine Learning in Search

Perhaps the best-known use of machine learning in search is Google’s own RankBrain, an algorithm that helps the search engine better understand the relevance and context of – and the relationship between – words.

Machine learning enables Google to understand the idea behind the query.

Machine learning allows the algorithm to continuously expand that understanding as new words and queries are introduced.

And as algorithms get better at determining which content best meets the needs of each searcher, we are being challenged to create content that meets those needs – and to optimize it so that relevance is clear.

It’s no coincidence that as we’re experiencing this explosion in data, interest in SEO is growing, as well.

SEO & Data Science

SEO has grown to be a viable, respectable mainstream marketing career.

As I write this, there are 823,000 people on LinkedIn with “SEO” in their profile and 8,600 who specifically categorize their core service offerings as SEO.

Looking worldwide, those figures balloon to 3.2 million and 25,000, respectively.

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But this is just a small sampling of the SEO industry.

There are those in SEO who identify as content marketers, digital marketing strategists or practitioners, site developers, analytics pros, consultants, advisors, and more.

Our industry is massive in size and scope, as SEO now touches nearly every aspect of the business.

So much more is being asked of SEO professionals now, thanks to that massive increase in data we have to deal with.

Yet according to our research at BrightEdge, only 31.5% of organizations have a data scientist at their company.

Working alongside machine learning rather offers tech-savvy SEO professionals a number of important advantages.

1. Enhanced Performance in Your Field of Specialization

Employers and clients alike are driven by results.

Do you know how to use the machine-learning-powered tools in your area of specialization?

Whether in paid search, technical SEO, content creation and optimization, link building or some other facet of SEO, those who can prove superior performance through the use of machine-learning-enabled SEO tools are increasing their own value.

2. Start Ahead & Stay Ahead

Search is a live auction. If you’re waiting to see what customers think and only then getting ready to respond, you’re already behind.

Machine-learning-powered tools enable marketers to activate real-time insights, to personalize and optimize content in the moment for each users’ individual needs.

3. Economies of Scale

You are exponentially more valuable as an SEO practitioner and leader if you can demonstrate the ability to scale your efforts.

The real power of machine learning is in its ability to convert more data than we know what to do with into actionable insights and automated actions that marketers can use to really move the needle.

To do that is hard.

For example, to build BrightEdge Autopilot we had to process over 345 petabytes of data over the course of many years to help fine-tune machine learning and automated products.

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Machines aren’t angling for a promotion; they don’t harbor preconceptions or care about past mistakes.

They are entirely subjective, taking opinions and personalities and other potential bottlenecks out of the process of data evaluation.

What marketers are left with are pure, accurate data outputs that can then be activated at scale to improve search visibility and interactions with customers.

4. Room to Grow

Mastering your SEO toolset gives you more room to grow in your profession, and as a person who just so happens to love the work you do.

Machine learning, in particular, empowers us to reap insights from larger datasets and gives us access to far more intelligence than when we could only learn from that we manually analyzed ourselves.

It is your specialized insight and industry knowledge that determines which outputs are useful and how they should be applied.

Machine learning can tell you very quickly how your audience’s behaviors have changed during a major market disruption, such as our recent experience with COVID-19.

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But how you interpret and respond to those changes is still very much the domain of marketing and SEO professionals.

Machine learning can help you recognize patterns in visitor behavior that point to opportunities and areas in need of improvement.

What technology cannot do is replace the creative and analytical human thought process and experience that determines the best next steps to take in response to those insights.

The people of SEO cannot be replaced. In fact, they’re more important than ever.

The tools we use may be quite sophisticated; machine-learning-enabled tools can even make decisions and implement optimizations.

However, it is the people of SEO who drive the creative and analytical processes that machines simply cannot replace:

  • Creative analysts.
  • Data scientist (who control input into machines).
  • Analytics.
  • Content producers.
  • Culture builders and success evangelists.
  • Expert users who facilitate sales and help customers.
  • Strategic planning across digital channels.

And there are agile marketers who may do any combination of the above.

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They are key in facilitating collaboration with other digital departments to ensure a truly holistic SEO strategy.

In their HBR article Collaborative Intelligence: Humans and AI Are Joining Forces, H. James Wilson and Paul R. Daugherty explain the three key roles humans undertake in every interaction with machine-learning-powered technology:

  • Train: We need to teach the machine to perform certain tasks.
  • Explain: We must make sense of the outcome of the task, especially if it is unexpected or counterintuitive.
  • Sustain: It is up to us to ensure that the technology is used logically and responsibly.

Applying this lens to our SEO tech, we see these three tenets hold true.

We need to decide which SEO tasks to intelligently automate and give our tools the proper input.

We need to take the output and make sense of it, focusing only on those insights with business-building potential.

We are responsible for ensuring that searcher privacy is protected, that the value of the technology outweighs the cost, and that it is otherwise being made good use of.

You can build your value as an SEO and learn to work more effectively with machine-learning-powered tech by building these skills:

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  • Data proficiency: According to Stanford researchers, the share of AI jobs grew from 0.3% in 2012 to 0.8% of total jobs posted in the U.S. in 2019. AI labor demand is growing, especially in high-tech services and the manufacturing sector.
  • Communication: As the arbiter of so much customer data, it is critical that we communicate key insights and value in ways other department heads and decision-makers can understand.
  • Agility: More than a trait or quality, agility is a skill developed through constant experimentation.

Embracing machine learning and automation means building synergy with human creativity and skills.

It can make us more creative and effective by uncovering SEO insights and patterns we would never have recognized otherwise.

It can help us discover new topics, identify content gaps, optimize for specific types of queries and results, and more.

What’s more, it can save vital time on tasks that are too time-consuming, too repetitive and laborious, so we can scale performance.

And as that happens, we develop new skills and progress also as part of a symbiotic relationship between people and technology.

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How to Improve Customer Satisfaction

A business–what does it run on? Customer feedback is the primary metric that represents the entire business process, and it’s a success. 

If you want your business to grow, you need to grow your customer base. And how does one do that? Well, that’s simple–you tend to their needs and exceed their desires. 

In this article, we will cover how to improve customer satisfaction. 

So keep reading to learn more.

improve.jpg

Customer > Problem

Frustration is a natural part of business, and it’s sort of the notion for doing things right. However, emotional dissidence can often cloud our judgment, and prevent us from providing the best possible service to those who matter. 

Problems are bound to arise, but they should not be a propeller for your emotional lashing out upon your customer base.

If a customer used a product wrongly, damaged it, reviewed it honestly – this can still be a victory for you. Given that you react in a calm, mature, and respectable manner. 

If something can be replaced, don’t seek out compensation. Remorse leads to great changes. If anything, they might be eager to purchase other things or compensate you regardless. 

Carry out your interactions with a smile, and they shall smile back. IF somebody is using your service, they should enjoy it. And that’s your job.

Personalize

It is the day of automation, delegation, and simplification. It might seem that robotic integration is the way to go, and perhaps it is. But that should not sway us from providing a personalized experience for the customer. 

They love your products, but when do they get to feel that the products are theirs? Provide them with a personal touch. Welcome them when they visit, use data to target them specifically at a persona level. Invite them by their name. 

Show a human face behind the automated environment. Answer their queries with personalized responses. Your customers don’t want auto-generated responses, they want a human funnel that leads them to make the right decision on their own. 

Don’t force them. Show them that they already want to interact with you.

More for Less

Cutting costs is a given, but it can come at increased costs in other aspects of your business. If you can provide the best possible product at an affordable price, then why not do that? Not only will your customers reciprocate with purchase, but they will do it gladly. 

Discount your loyal customers, provide them with benefits for patronizing your business for many years before. Welcome-back offers might seem like a great idea to pull in dissatisfied customers, but the whole point is that they lost their satisfaction. 

You don’t want that. You want them to be satisfied all throughout. A satisfied customer is loyal, which means you leave on good terms and can interact once again in the near future.

Learn how a decoupling process helps in improving customer satisfaction.

Happy Employees = Happy Customers

It might seem irrelevant, but it’s really not. While focusing on only satisfying your customer, you need to understand how your employees play into this experience. An unsatisfied employee will lead to unsatisfied customers. If they are scaring away customers with their poor attitude, there’s a great issue at play. An issue that you have to resolve. 

Don’t let your employees give you an eye-candy, and only work when you’re around. It’s not your job to do everything, that’s why you have a team. So here are some ways to motivate your team:

  1. Be transparent, supportive, and respectful
  2. Pay well and on-time
  3. Support personal and professional growth
  4. Show them importance in the company, and seek opinions
  5. Provide perks and benefits to outstanding employees
  6. Change the environment to be more conducive to effective work
  7. Don’t bind employees to a single-mode of execution

When your employees are happy and motivated, the effects will naturally spread into the feeling for your customers. And if they can relate and communicate well, that’s the most important thing that can occur in your business. Capable and clear communication between your employees and your customers.

Round the Clock Support

In the consumer world, a fast response is a completely valid reason for choosing one company over the other. And the only way to achieve this is via round the clock support, especially if you tailor to a large customer base.

The simplest way to acquire this level of involvement is by hiring multiple customer reps and have them work shifts. If your budget does not allow that, delegate the customer support to freelancers or specialized agencies that uphold the greatest standards for support. 

You can also use a chatbot that will help you funnel customers into FAQs and other sections that they might find useful. But remember, a non-human approach is often diminished via the human interaction that a customer seeks.

If you can’t provide 24-hour support, think about live chat throughout your work hours. This way your customers don’t have to wait two days just to ask a simple question. Consumers love to live chat, and it will significantly increase your company revenue. In fact, companies that have live chat, outperform all other companies by a large margin.

How to Improve Customer Satisfaction? Simple.

Now that you know how to improve customer satisfaction, you can quickly ascertain that for customers to be satisfied, you need to satisfy their needs, and exceed their desires. 

Business is not passive in any shape or form. It’s a proactive relationship of multiple commercial parties, which can be tended to in a variety of ways. If you neglect customer satisfaction, you are neglecting your entire business. 

via Taking Care of the Customer: How to Improve Customer Satisfaction

 

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Augmented Search Queries Using Knowledge Graph Information

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What are Augmented Search Queries?

Last year, I wrote a post called Quality Scores for Queries: Structured Data, Synthetic Queries, and Augmentation Queries. It told us Google may look at query logs and structured data (table data and schema data) related to a site to create augmentation queries, and test information about searches for those queries by comparing them to original queries for pages from that site. If search results from the augmentation queries do well in evaluations compared to search results from original query results, searchers may see search results combine results from the original queries and the augmentation queries.

Around the time that patent was granted to Google another patent that talks about augmented search queries was also granted to Google, and is worth talking about at the same time with the patent I wrote about last year. It takes the concept of adding results from augmented search queries together with original search results, but it has a different way of coming up with augmented search queries, This newer patent that I am writing about starts by telling us what the patent is about:

This disclosure relates generally to providing search results in response to a search query containing an entity reference. Search engines receive search queries containing a reference to a person, such as a person’s name. Results to these queries are oftentimes not sufficiently organized, not comprehensive enough, or otherwise not presented in a useful way.

Augmentation from the first patent means possibly providing additional information in search results based upon additional query information from query logs or structured data from a site. Under this new patent, augmentation comes from recognizing that an entity exists in a query, and providing some additional information in search results based upon that entity.

This patent is interesting to me because it takes an older type of search – where a query returns pages in response to the keywords typed into a search box, with a newer type of search, where an entity is identified in a query, and knowledge information about that entity is reviewed to create possible augmentation queries that could be combined with the results of the original query.

The process behind this patent can be described in this way:

In some implementations, a system receives a search query containing an entity reference, such as a person’s name, that corresponds to one or more distinct entities. The system provides a set of results, where each result is associated with at least one of the distinct entities. The system uses the set of results to identify attributes of the entity and uses the identified attributes to generate additional, augmented search queries associated with the entity. The system updates the set of results based on one or more of these augmented search queries.

A summary of that process can be described as:

  1. Receiving a search query associated with an entity reference, wherein the entity reference corresponds to one or more distinct entities.
  2. Providing a set of results for the search query where the set of results distinguishes between distinct entities.
  3. Identifying one or more attributes of at least one entity of the one or more distinct entities based at least in part on the set of results.
  4. Generating one or more additional search queries based on the search query, the at least one entity, and the one or more attributes.
  5. Receiving an input selecting at least one of the one or more additional search queries and providing an updated set of results based on the selected one or more additional search queries, where the updated set of results comprises at least one result, not in the set of results.

The step of generating one or more additional search queries means ranking the identified one or more attributes and generating one or more additional search queries based on the search query, the at least one entity, the one or more attributes, and the ranking.

That ranking can be based on the frequency of occurrence.
The ranking can also be based on a location of each of the one or more attributes concerning at least one entity in the set of results.

augmented search queries matt damon

This process can identify two different entities in a query. For instance, there were two versions of the Movie, the Planet of the Apes. One was released in 1968, and the other was released in 2001. They had different actors in them, and the second was considered a reboot of the first.

When results are generated in instances where there may be more than one entity involved, the search queries provided may distinguish between the distinct entities. They may identify one or more attributes of at least one entity of the one or more distinct entities based at least in part on the set of results. Augmented search queries may be generated for “one or more additional search queries based on the search query, the at least one entity, and the one or more attributes.”

This patent can be found at:

Providing search results using augmented search queries
Inventors: Emily Moxley and Sean Liu
Assignee: Google LLC
US Patent: 10,055,462
Granted: August 21, 2018
Filed: March 15, 2013

Abstract

Methods and systems are provided for updating a set of results. In some implementations, a search query associated with an entity reference is received. The entity reference corresponds to one or more distinct entities. A set of results for the search query is provided, and the set of results distinguishes between distinct entities. One or more attributes for at least one entity of the one or more distinct entities are identified based at least in part on the set of results. One or more additional search queries are identified based on the search query, the at least one entity, and the one or more attributes. An input selecting at least one of the additional search queries is received. An updated set of results is provided based on the selected additional search queries. The updated set of results comprises at least one result not in the set of results.

Some Additional Information About How Augmented Search Queries are Found and Used

A couple of quick definitions from the patent:

Entity Reference – refers to an identifier that corresponds to one or more distinct entities.

Entity – refers to a thing or concept that is singular, unique, well defined, and distinguishable.

This patent is all about augmenting a set of query results by providing more information about entities that may appear in a query:

An entity reference may correspond to more than one distinct entity. An entity reference may be a person’s name, and corresponding entities may include distinct people who share the referenced name.

This process is broader than queries involving people. We are given a list in the patent that it includes, and it covers, “a person, place, item, idea, topic, abstract concept, concrete element, another suitable thing, or any combination thereof.”

And when an entity reference appears in a query, it may cover a number of entities, for example, a query that refers to John Adams could be referring to:

  • John Adams the Second President
  • John Quincy Adams the Sixth President
  • John Adams the artist

Entity attributes

In addition to having an entity in an entity reference in a query, we may see a mention of an attribute for that entity, which is “any feature or characteristic associated with an entity that the system may identify based on the set of results.” For the John Adams entity reference, we may also see attributes included in search results, such as [second president], [Abigail Adams], and [Alien and Sedition Acts].

It sounds like an entity selection box could be shown that allows a searcher to identify which entity they might like to see results about, so when there is an entity in a query such as John Adams, and there are at least three different John Adams that could be included in augmented search results, there may be clickable hyperlinks for entities for a searcher to select or deselect which entity they might be interested in seeing more about.

Augmented Search Queries with Entities Process Takeaways

When an original query includes and entity reference in it, Google may allow searchers to identify which entity they are interested in, and possibly attributes associated with that entity. This brings the knowledge graph to search, using it to augment queries in such a manner. A flowchart from the patent illustrates this process in a way that was worth including in this post:

augmented search queries flowchart

The patent provides a very detailed example of how a search that includes entity information about a royal wedding in England might be surfaced using this augmented search query approach. That may not be a query that I might perform, but I could imagine some that I would like to try out. I could envision some queries involving sports and movies and business. If you own a business, and it is not in Google’s knowledge graph you may end up missing out on being included in results from augmented search queries.

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Content Marketing: it’s All About Targeting

Early last year, content marketing surpassed link building, when it comes to search volume. It’s not something new, but apparently, the term is sufficiently self-explanatory at CEO- and manager level to have earned content marketing a place on the product menus of sales-driven SEO and online marketing agencies.

In my opinion, there are two types of content marketing. The traditional, century-old form is to publish content to acquire customers. More recently, publishing content to acquire links has also been labeled as content marketing, but I think that this is fundamentally different from the original. Sure, it can eventually lead to the same results (more sales), but the initial goals are different. You’re either marketing your product through content, or you’re marketing your content. Followed the best Telegenic Marketing.

Build it, and they will come?

Simply create compelling content and links will follow, right? In an ideal world, yes. But not in the real world.

I often see people trying to use content in their marketing strategy, then struggling with it, quickly followed by giving up when the results are unsatisfying and finally stating that “content marketing doesn´t work for them”.

Well, everyone can use content to effectively build links in a profitable way, but only with the right strategy. When defining the most suitable approach, this is the process I always follow.

Step 1: Situation analysis

Different situations require different approaches. Try to find out what you need most in your situation, by taking a close look at your competition with tools like CognitiveSEO or MajesticSEO. Not to see what you can copy, but for a SWOT analysis. You know, just like in old school marketing. To identify weaknesses in your link profile that need to be addressed, but also to spot opportunities or threats.

If it turns out that your link profile lacks relevance (you’ve got lots of links, but almost zero from your own industry), you’ll need a different approach than when you simply need volume. And the needs of an established, authoritative website are different from a relatively new site.

If you have defined your needs, you can move on the the next phase.

Step 2: Concept

With a clear SWOT in mind, you can try to come up with an idea that might help you to reach your goals.

Why do people share?

Before you start thinking about ideas that you can use, it is very important to get a crystal clear image of your target audience. Who are they and, more importantly, what makes your audience share stuff?

This usually differs between industries and between website types. For example, a travel affiliate site shows linking and sharing behaviour that is different from a finance blogger. And keep in mind: websites or companies don’t share things, people do, and that’s why there are so many blogs online now a days, since is not difficult to create one, and there are sites like HowToCreateABlog.org that help people that want to create a blog and share their thoughts and content.

In general, there are five reasons why people share stuff. Self definition is without a doubt the most important sharing motivator. You are what you share, and people continuously build their personal brand online. Just take a look at what you share online. I can probably get quite a good picture of who you are just by analyzing what you’ve shared in the past.

Another sharing motivator is Personal benefit. This does not necessarily have to be a financial payment, but sharing something because you want to get something in return, to create goodwill, or simply to get noticed are personal benefits as well.

Altruism (often reciprocal altruism, since real altruism is very scarce), Connectedness (maintaining relationships) and Evangelism are other reasons for people to share things online.

If you’re interested in finding out more about why people share stuff, I’d recommend reading this study from the New York Times.

Not all shares are created equal

With that in mind, it is also important to think about what attracts the right kind of shares. A photo of a cute cat might get thousands of likes on Facebook without attracting a single link, while an extensive resources earns hundreds of links but only a handful of shares or tweets.

Just take a look at the list below and ask yourself what you’d prefer. Usually the more effort a share takes, the more valuable it is.

* Facebook Like: “Here’s another photo of a cute cat.”
* Retweet: “Someone I trust likes it, so it’s probably awesome.”
* Facebook share: “It’s good enough to make me break my pattern of clicking the like button.”
* Tweet: “You’ve made me say something on Twitter.”
* Facebook post: “I have been triggered enough to create a post on Facebook.”
* Regular link: “I just logged in to WordPress / Tumblr / used DreamWeaver / whatever and unleashed my HTML-knowledge on something that exceeded 140 characters.”
* Google Plus: “Oh Google, I love you.”

I’m not saying that you should focus on links only, but selecting a concept that’s only capable of getting Likes or Shares on Facebook is probably not your best option, and the use of marketing strategies, like the use of digital menu boards displays to show products and services to the public so they can learn find the best services for their needs.

Personas?

For individual content items, you probably don’t need to create full-blown persona profiles, but you should definitely think about it.

Ask yourself this: “If I create this, who will link to it? And why?”. If you’re not able to answer this straight away, you’re probably better off creating persona profiles first.

Step 3: Creation

Once you have a clear picture of your target audience, you will be able to create content that is much more effective.

Content requirements

You need content that is made to stick. Or rather, content that is made to be shared.

Success is almost a guarantee when your content is:
Simple
Trustworthy
Recognizable / identifiable
Unique / unexpected
Commerce is secondary (at most)
Triggers action-emotions

There’s already been written a lot about these concept requirements (I’d recommend checking out Ross Hudgens’ Content Marketing Checklist), but the last one could use some additional elaboration.

Target emotions

If you analyse different examples very succesful content, you will find that there’s one common denominator: they all trigger action-emotions.

Our normal behaviour is to digest content. Read, see, view, move on. But strong emotions can make people act different from their normal behaviour. It can make people take action, in stead of proceeding with their passive, digestive behavior. The stronger the emotion, the more effort someone will take to get the word out (Like vs. Link).

If you target the right emotions, you might be able to (subtly) persuade them to take action, by sharing your content. This might sound manipulative, but this is all what marketing is about: persuading people into taking specific actions.

There are dozens of different emotions, and some are more easy or effectively to target than others. In general, most emotions can be devided into six different categories; Pride, Pleasure, Passion, Fear, Anger and Sadness.

emotions

Keep in mind that there are also a few emotions that you rather want to avoid, including Lust, Relaxation, Boredom, Regret, Stress, Guilt and Embarassment. These are all emotions that most people prefer to exerience privately, and not in public.

Step 4: Promotion

If you have put enough effort in the first three stages of this process, the promotion will be a breeze. You knew from the start who you’d be targeting, which made it easier for you subtly make them share your content by triggering their emotions.

Sure, you’ll still need to send out dozens of emails and make a few promotional calls. And you’ll probably also want to spend some ad budget on Facebook, StumbleUpon, Outbrain or whatever is relevant in your situation. But all of this will be much more effective and lead to better results when your content is carefully crafted for your situation, and properly targeted at the right audience. Which will save you time and budget for the next content item.

tl;dr

1. Define your needs
2. Find out what makes your target audience share (and link!)
3. Create something that matches #1 with #2
4. Promote the hell out of it
5. Rinse and repeat

Need help?

As you can see, content marketing is a *lot* more than just ‘creating good content’. Especially when you don’t have a lot of experience with creating and promoting content, it can definitely be overwhelming. It is also something that you have to budget for carefully, otherwise you could incur a debt right off the bat, which is no good. If this were to happen don’t let it get out of hand, specially if you’re just getting started. Businesses are very volatile at the very beginning.

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Breaking down the push and pull of expansion, consolidation across the martech app ecosystem

Everyone in our industry knows that the growth rate among marketing technology applications has been exponential for years now. The 2020 Marketing Technology landscape released last month included 8,000 solutions. There were fewer than 200 logos on the chart in 2011, which means we’ve seen a 5,233% increase in martech solutions in less than a decade.

Even in the current economic crisis and the impact it will have over the next 18 months, some martech companies may see gains. Forrester reported this month it expects marketing spend to drop 28% in the U.S. by the end of 2021, with CMO budgets losing $222 billion. And yet, Forrester predicts tech spend will not only hold, but expects data and analytics, advertising technology and marketing automation to grow by 2% — a very slight growth, but still growth.

And within all of this growth across our industry, two (what seems like) opposing realities exist, according to MarTech Conference Chair and editor of Chiefmartec.com Scott Brinker: There is a massive consolidation in platforms; and there is a massive expansion and diversification of apps.

The push and pull of consolidation versus expansion

“Everyone is surprised by how fast it has grown,” said Brinker about his Marketing Technology Landscape super graphic, “One of the questions I’m constantly asked is why?”

Brinker doesn’t believe there is a single force that can explain the massive growth across the martech industry, and that if you try to attribute it to one driving factor, the evidence won’t support it. Instead you have to take multiple factors into consideration. There is also the another layer to this growth: the birthrate of martech apps versus their death-rate.

“Anyone can launch a software product. The question is can anyone sustain a business,” said Brinker.

And then there are the two driving forces that keep showing across the marketing app ecosystem: The push and pull of consolidation versus expansion.

“The ‘paradox’ of consolidation and expansion, in martech and in SaaS more generally, is then simply explained by math,” writes Brinker in his deep-dive exploration of the platform dynamics driving martech app expansion and consolidation, “Platforms consolidate while spawning more apps than they remove. The net number of apps in the world grows, even while there is intense competition driving consolidation further down in the spectrum.”

From ChiefMartec.com

Brinker notes that one of the key ways platforms compete with each other is by enabling more apps than their competitors, “The more intense the competition is between platforms, driving their own consolidation, the more apps they help create.”

In other words, the industry simply can’t help itself — as long as major platforms continue to compete, the app economy will grow.

“Its not a paradox,” writes Brinker, “It’s the very structure of business in the cloud.”

What does it mean for marketing technologists

One way to consider what’s happening across the martech app landscape is to think of it in terms of our media and entertain options. Once upon a time, consumers had four channels they could access through their television, along with maybe a few local studio channels that came in fuzzy if your TV antenna wasn’t placed just right. And then, cable and satellite TV came along — bringing with it an explosion of entertainment options.

And now? There are streaming options, OTT platforms, social networks pushing out original content. YouTube channels. TikTok. Quibi. All exponential growth that has resulted in the ability to both layer and integrate these options, and if you’re a content producer all you need is a smartphone — much like the developers building specialized apps that don’t necessarily even have to know how to code with so many cloud platforms offering no-code and low-code capabilities.

In the same way we get to pick and choose our, sometimes very niche, entertainment viewing options, marketing technologists have a smorgasbord of solutions: Starting with their foundational platforms and building out to the various specialized and custom apps that can be integrated.

From ChiefMartec.com

“Platforms have truly embraced being platforms,” said Brinker, “With third-party integrations, we all end up making the customer happy. Instead of looking at [other martech] companies as competitors, they see them as complementary integrations.”

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