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What is AI Marketing? A Complete Guide

Many companies - and the marketing teams that support

them - are rapidly adopting intelligent technology solutions
to encourage operational efficiency while improving the customer
experience. These intelligent solutions often come in the form
of Artificial Intelligence (AI) marketing platforms.
Through these platforms, marketers can gain a more nuanced,
comprehensive understanding of their target audiences.
The artificial intelligence-driven insights gathered through
this optimization process can then be used to drive conversions,
while also easing the workload for marketing teams.

      What is AI (Artificial Intelligence) Marketing?

Data Analysis: Collecting and sifting through large amounts of
marketing data from various campaigns and programs that would
otherwise have to be sorted manually.

Natural Language Processing (NLP): Creating human-like language
for content creation, customer service bots, experience
personalization and more.

Media Buying: Predicting the most effective ad and media
placements for a business in order to reach their target
audience and maximize marketing strategy ROI.

      Types of AI Marketing Solutions

It’s clear that artificial intelligence holds a vital role in
helping marketers connect with consumers. The following
components of AI marketing make up today’s leading solutions
that are helping to bridge the gap between the vast amounts
of customer data being collected and the actionable next steps
digital marketers can take in their future campaigns:

      Machine Learning

Machine learning is driven by artificial intelligence,
which involves computer algorithms that can analyze information
and improve digital marketing campaigns automatically through
experience. Devices that leverage machine learning analyze new
information in the context of relevant historical data, which
can inform digital marketing campaigns based on what has or
hasn’t worked in the past.

     Big Data and Analytics
The emergence of digital media has brought on an influx of
“big data”, which has provided opportunities for digital
marketers to understand their efforts and accurately attribute
value across channels. This has also led to an over-saturation
of data, as many digital marketers struggle to determine which
data sets are worth collecting. AI marketing can help parse
through all that data at lightspeed, filtering it down to its
essentials and not only analyzing it but also recommending the
best elements of future digital marketing campaigns.

     AI Marketing Platforms & Tools

Effective AI-powered marketing solutions provide digital
marketers with a central platform for managing the huge amounts
of data being collected. These AI marketing platforms have the
ability to glean insightful marketing intelligence from your
target audience so you can make data-driven decisions about how
to best reach them. For example, frameworks such as Bayesian
Learning and Forgetting can help marketers gain a clearer
understanding of how receptive a customer is to a specific
digital marketing effort.

               Challenges for AI Marketing

    Modern marketing relies on an in-depth understanding of
    customer needs and preferences, and the ability to act on
    that knowledge quickly and effectively. The ability to make
    real-time, data-driven decisions has brought AI marketing
    solutions to the forefront for marketing stakeholders.
    However, marketing teams must be discerning when deciding
    how to best integrate AI into their campaigns and operations.
    The development and use of AI marketing tools is still in
    its early stages. Therefore, there are a few challenges to
    be aware of when implementing AI into your digital marketing
    strategy.

      Training Time and Data Quality

    AI marketing tools do not automatically know which actions
    to take to achieve marketing goals. They require time and
    training, just as humans do, to learn organizational goals,
    customer preferences, historical trends, understand overall
    context, and establish expertise. This learning process
    also requires data quality assurances. If your AI marketing
    tools are not trained with high-quality data that is accurate
    , timely, and representative, you’ll end up with inaccurate
    data decisions that don’t truly reflect consumer desires,
    making your shiny new AI marketing tool nothing more than a
    toy.

      Privacy

    Consumers and regulating bodies alike are cracking down on
    how organizations use their data. Digital marketing teams
    need to ensure they are using consumer data ethically and in
    compliance with standards such as GDPR while implementing an
    AI marketing strategy, or risk heavy penalties and reputation
    damage. Unless your AI marketing tools are specifically
    programmed to observe specific legal guidelines, they may
    overstep in what is considered acceptable in terms of using
    consumer data for marketing personalization.

      Getting Buy-In

   It can be difficult for digital marketing teams to demonstrate
   the value of AI marketing investments to business stakeholders
   . While KPIs such as ROI and efficiency are easily
   quantifiable, showing how AI marketing has improved customer
   experience or brand reputation can be less obvious.
   With this in mind, digital marketing teams need to ensure they
   have the right measurement tools to attribute these
   qualitative gains to AI investments.

      Deployment Best Practices

   Because AI marketing is a newer tool in the digital marketer’s
   toolbox, definitive best practices haven’t yet been
   established to guide marketing teams’ initial deployments.
   Every digital marketing team should think about the long-term
   effects of implementing an AI marketing strategy, not just the
   short-term benefits they could reap.

      Adapting to a Changing Marketing Landscape

   With the emergence of AI marketing comes a disruption in the
   day-to-day marketing operations. Marketers must evaluate which
   jobs will be replaced and which jobs will be created. One
   study suggested that nearly 6 out of every 10 current
   marketing specialist and analyst jobs will be replaced with
   marketing technology.

      How to Use AI in Marketing

   It’s important to begin with a thorough plan when leveraging
   AI in marketing campaigns and operations. This will ensure
   marketing teams minimize costly challenges and achieve the
   most value from their AI investment in the least amount of
   time.

          Establish Goals
   As with any marketing program, it is important that clear
   goals and marketing analytics are established for your AI
   marketing program from the outset. Start by identifying areas
   within campaigns or operations that could stand to be improved
   , such as segmentation. Then establish clear KPIs that will
   help illuminate how successful the AI-augmented marketing
   campaign has been – this is especially important for
   qualitative goals such as “improve customer experience.”

          Data Privacy Standards
   At the outset of your new marketing program, be sure that
   your AI marketing platform will not cross the line of
   acceptable data use in the name of data personalization.
   Be sure privacy standards are established and programmed into
   your AI marketing platforms as needed to maintain compliance
   and consumer trust.

          Data Quantity and Sources
In order to get started with AI marketing, digital marketers
typically need to have a vast amount of data at their disposal.
This data will train the AI marketing tool in customer
preferences, external trends, and other factors that will impact
the success of AI-enabled marketing campaigns. This data can be
taken from the organization’s own CRM, previous marketing
campaigns, and website data. Additionally, marketers may
supplement this with second and third-party data, which can
include location data, weather data, and other external factors
that may contribute to a purchasing decision.

          Acquire Data Science Talent
Many marketing teams lack employees with the necessary data
science and AI expertise, making it difficult to work with vast
amounts of data and deliver insights. To get AI marketing
programs off the ground, organizations should work with
third-party organizations that can assist in the collection and
analysis of data to train their tools for optimal performance
and facilitate ongoing maintenance.

     Maintain Data Quality
As machine learning and AI marketing programs consume more data,
they will learn how to make accurate, effective decisions.
However, if the data being fed to your AI marketing program is
not standardized and error-free, the insights will not be useful
and can actually cause decisions that hurt your bottom line
rather than help it. Prior to implementing any AI marketing
programs, marketing teams must coordinate with data management
teams and other lines of business to establish processes for
data cleansing and data maintenance. When doing so, consider the

seven essential data dimensions:

• Timeliness

• Completeness

• Consistency

• Relevance

• Transparency

• Accuracy

• Representativeness

       Create an Integrated AI Marketing Strategy
Most digital marketers find their AI marketing tools are
especially effective when integrated with their existing
marketing strategy, rather than being used as a stand-alone
tactic. AI marketing tools create opportunities to optimize
steps in a marketing strategy that might currently be
labor-intensive, such as data analysis, or have a risk of
inaccuracy, such as attribution.

By incorporating AI to fill in these “blind spots”,
digital marketers can not only leverage these powerful
forward-thinking methods to take their marketing to the next
level but also build on the foundation of effective digital
marketing methods they’ve used in the past.

        Selecting an AI Platform
Selecting the right platform or platforms is a crucial step in
getting an AI marketing program off the ground. Marketers should
be discerning in identifying the gaps that the platform is trying
to fill and select solutions based on capabilities.
This will revolve around the goal marketers are trying to achieve
– for example, speed, and productivity goals will require
different functionality than tools used to improve overall
customer satisfaction with AI.

Benefits of Leveraging AI (Artificial Intelligence) in Marketing
   There are a myriad of use cases for incorporating AI marketing
   into your digital marketing programs, and each of these use
   cases yields different benefits. For example, AI marketing
   can be an asset in areas such as risk reduction, increased
   speed, greater customer satisfaction, increased revenue,
   and more. Benefits may be quantifiable (number of sales) or
   not quantifiable (user satisfaction). There are a few
   overarching benefits that can be applied across AI marketing
   use cases:

       Increased Campaign ROI
If leveraged correctly, marketers can use AI marketing to
transform their entire marketing program by extracting the most
valuable insights from their datasets and acting on them in
real-time. AI platforms can make fast decisions on how to best
allocate funds across media channels or analyze the most
effective ad placements to more consistently engage customers,
getting the most value out of campaigns.

   Better Customer Relationships & Real-Time Personalization
AI marketing can help you deliver personalized messages to
customers at appropriate points in the consumer lifecycle.
It can also help digital marketers identify at-risk customers
and target them with information that will get them to re-engage
with the brand.

   Enhanced Marketing Measurement
Many organizations have trouble keeping pace with all of the
data digital marketing campaigns produce, making it difficult
to tie success back to specific campaigns. Dashboards that
leverage AI marketing allow for a more comprehensive view into
what is working so that it can be replicated across channels
and budgets allocated accordingly.

   Make Decisions Faster
AI marketing is able to conduct tactical data analysis faster
than its human counterparts and use machine learning to come to
fast conclusions based on campaign and customer context.
This gives team members time to focus on strategic initiatives
that can then inform AI-enabled campaigns. With AI marketing,
digital marketers no longer have to wait until the end of a
campaign to make decisions, but can use real-time analytics to
make better media choices.

    7 Examples of AI (Artificial Intelligence) in Marketing
AI marketing is being used in digital marketing initiatives in a
multitude of use cases, across a broad array of industries.
Industries leveraging AI marketing and its optimization
capabilities include financial services, government,
entertainment, healthcare, retail, and more. Each AI marketing
use case offers different results, from customer retention
improvements to campaign performance, to enhanced customer
experience, or greater efficiency in marketing operations.

There are numerous ways businesses can take advantage of AI
marketing and machine learning to create a more comprehensive
marketing plan. Consider the following:

1. Bidding on Programmatic Media Buys
A problem that marketing teams often encounter is deciding where
to place advertisements and messaging. Marketing teams can
create informed plans based on user preferences, but these teams
are often not flexible or agile enough to alter the plan in
real-time based on the latest consumer information. AI marketing
is being used by digital marketers to mitigate this challenge
through programmatic advertising.

Programmatic platforms leverage machine learning to bid on ad
space relevant to target audiences in real-time. The bid is
informed by data such as interests, location, purchase history,
buyer intent, and more. This enables digital marketing teams to
leverage AI marketing to target the right channels at the correct
time, for a competitive price. Programmatic buying exemplifies
how machine learning can increase marketing flexibility to meet
customers as their needs and interests evolve.

2.   Select the Right Message
Across channels, different consumers respond to different
messages – some may resonate with an emotional appeal, some
humor, others logic. Machine learning and AI marketing can track
which messaging consumers have responded to and create a more
complete user profile. From there, marketing teams can serve
more customized messages to users based on their preferences.

For example, Netflix uses machine learning to understand the
genres a certain user is interested in. It then customizes the
artwork that the user sees to match up with these interests.
On the Netflix Tech Blog, the author explains how Netflix
leverages AI tools and algorithms to determine which artwork
will most entice a viewer to watch a certain title, saying:

“Let us consider trying to personalize the image we use to
depict the movie Good Will Hunting. Here we might personalize
this decision based on how much a member prefers different
genres and themes. Someone who has watched many romantic movies
may be interested in Good Will Hunting if we show the artwork
containing Matt Damon and Minnie Driver, whereas, a member who
has watched many comedies might be drawn to the movie if we use
the artwork containing Robin Williams, a well-known comedian."

When AI marketing tools and machine learning are used, these
platforms can gather valuable data on customers that allow
marketing teams to increase conversion rates and improve the
customer’s experience. Marketing teams can then analyze all of
this data to create a more nuanced view of the customer, even
considering additional factors such as if a user would have
watched a title regardless of the image, and how that plays into
future messaging.

3. Granular Personalization
A highly granular level of personalization is expected by today’s
consumers. Marketing messages should be informed by a user’s
interests, purchase history, location, past brand interactions,
and a host of other data points. AI marketing helps marketing
teams go beyond standard demographic data to learn about
consumer preferences on a granular, individual level. This helps
brands create curated experiences based on a customer’s unique
tastes.

For example, Spotify uses AI marketing tools to create customized
playlists based on what a customer has listened to in the past,
current hits across genres, and which music is being talked about
. It uses these datasets to create customized playlists for users
and to create genre playlists based on artists that appear in
conversation, in articles, etc. This data has helped Spotify to
become a top streaming service and emphasize customer experience
through personalization.

Another trend based on AI-enabled personalization is atomic
content. Here, AI learns customer preferences and pulls pieces
from a library of content to create a customized email or offer
for a client featuring relevant images, videos, or articles.

4.   Chatbots and Conversational Experiences
With the development of natural language processing through AI,
chatbots are now being used to augment customer service agents.
Customers with more basic queries can refer to chatbots which
will give immediate, accurate answers. They will be able to
leverage past questions and historical data to deliver
personalized results. This gives time back to customer service
agents to work on complicated requests that need more human
nuance.

5. Predictive Marketing Analytics
With so much data flowing into their organization every day,
marketing teams are having a hard time actually deriving insights
from it. AI marketing tools allow marketing teams to make the
most of this data using predictive analytics, which leverages a
combination of machine learning, algorithms, models, and datasets
to predict future behavior. This can help digital marketing
teams understand the types of products a consumer will be looking
for and when – allowing them to position campaigns more

For example, Amazon uses predictive analytics to suggest products
to consumers based on past purchases and behaviors, increasing
conversions and customer satisfaction. AI marketing tools can
also be used to help marketing teams more accurately track
attribution, allowing teams to see which campaigns contributed
most to ROI.

6. Marketing Operations
Another key use case for AI marketing tools is to increase
efficiency across various processes. AI can help to automate
tactical processes such as the sorting of marketing data,
answering common customer questions, and conducting security
authorizations. This allows marketing teams more time to work
on strategic and analytical work.

7. Dynamic Pricing
AI marketing can help make brands more competitive by enabling
dynamic pricing. AI platforms can suggest optimal prices for
products in real-time by evaluating huge quantities of
historical and competitive data. This strategy has been
especially effective in retail. It allows brands to adjust
prices to reflect demand for certain products, boost sales,
and edge out the competition.

        AI Marketing Predictions and Trends
While AI marketing tools are still largely new additions to the
marketing space, it promises to only grow in popularity. There
are a few AI trends marketers will see over the next few years
and should begin to adapt to:

AI is Growing:
Gartner has predicted that by 2022, AI will replace about 33% of
data analysts in marketing.
Tech giants realize the benefits and potential for AI. In 2016,
they were already spending on average between $20-$30 billion.
90 percent of this budget was focused on deployment and research.
Additionally, in 2020 Gartner predicted that more than 40% of
data science tasks will be automated

     Teams Will Scale Through AI
Marketing teams will be put under increased pressure to
demonstrate marketing value and ROI to executive stakeholders.
Teams will be able to leverage AI marketing solutions to drive
these targets and better allocate funds towards successful
campaigns, as well as providing the marketing metrics that
demonstrate the value of campaigns.

Marketing Leaders Who Don’t Leverage AI Will Be Replaced By
Those Who Do
According to Gartner, those responsible for marketing insights
will no longer be as competitive in this changing marketing
landscape. The majority of those surveyed by Gartner employ AI
solutions in their marketing strategy or are planning to.
Only 13 percent do not see a use for it in the next three years.

Breaking Down AI Marketing
No matter how large or small your marketing team is, AI marketing tools and machine learning programs can help increase productivity, ROI and efficiency, while also processing those mountains of data your team might not have time to wrestle with otherwise.

Even if your first foray into AI marketing is something as small as using a machine learning program to help write your email subject lines for your next digital marketing campaign, every little step towards an AI-powered future can help keep your brand ahead of the competition and crushing revenue goals all year long.

Additional Tips and Resources
Your AI Does Not Need Tickets to the Big Game
The Role of Predictive Analytics in Data-Driven Marketing
The Future of AI

Breaking Down AI Marketing
No matter how large or small your marketing team is, AI marketing
tools and machine learning programs can help increase
productivity, ROI and efficiency, while also processing those
mountains of data your team might not have time to wrestle with
otherwise.

Even if your first foray into AI marketing is something as small
as using a machine learning program to help write your email
subject lines for your next digital marketing campaign, every
little step towards an AI-powered future can help keep your
brand ahead of the competition and crushing revenue goals all
year long.

Additional Tips and Resources
Your AI Does Not Need Tickets to the Big Game
The Role of Predictive Analytics in Data-Driven Marketing
The Future of AI

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You heard right. Good marketing is good marketing, no matter the medium. There is no panacea of marketing, and the Internet is certainly not the end all or be all. While it is true, the Internet is the last place where someone of modest budget can compete with some of the largest players in marketing and win, this sort of profitable activity requires hard word and analysis just like any other marketing campaign.

Marketing is not sales. Marketing is the "art and science" of getting someone to see the value your product or service holds for them...to the extent that they desire to acquire it. You will needs sales to complete the cycle but marketing, as I have just defined it, is the basis of our Internet Marketing/Search Engine Optimization paper.

Marketing on the Internet is a lot like the Wild West of the 1800's on the North American continent. There are tons of opportunities all around but it takes a thinker to notice and exploit them. gone are the days when anyone could walk up to a venture capitalist and propose an "Internet Business Model" and end up with some sort of funding. I remember those days like they were yesterday (They really were) and many of my friends, rich with Venture Capital cash, went out and bought Ferrari's, big homes, lavish toys. Many of those same friends had to give all that stuff up because when folks realized that the Internet was not a wonderland but a new communication tool, they closed the cash spigots and the money went elsewhere...fast.

At the beginning of course! No marketing campaign will work without first performing a SWOT analysis. SWOT (Strengths, Weaknesses, Opportunities, Threats) are a bit beyond the scope of this site but the analogy does hold purpose in the Search engine optimization process. Internet Marketing is all about getting the consumer of your product to want it badly enough to take action...to do this, we first need to get in front of that potential consumer. The cheapest and fastest way you reach a ton of people legitimately is thorough search engine optimization, the process of refining your web site to rank well in the "Organic" or non-paid areas of a search engine or directory.

While it is important to be in as many different search engines and directories as possible, there are really only a dozen or so that will bring you an appreciable traffic. Having said that, one paying client from an obscure engine is worth exactly what you paid for it. Sine Google is at the present time, the king of search engines, we will spend quite a bit of time talking about things that make your site rank well with Google....but we will not talk exclusively about Google. When I do Search engine optimization for clients, I ALWAYS fine tune for the greatest amount of engines and directories, because I never know what will happen tomorrow and being #1 in the current "big dog" while hedging my bets for tomorrow's up-and-comers just makes sense to me....and helps me sleep better at night.

A case in point, the latest Google update, nicknamed the "Google Florida Update", actually resulted in a tremendous boost to all of my clients' rankings. There are several reasons for this phenomena, but the main ones are that I optimize for what really has value...content.

This website will provide you with all of the tools necessary to achieve top search engine positions if you study the tips, apply them and use the tools in the manner they were intended to be used. search engine optimization is not rocket science, it is simply the study of what make s a web site the most "relevant" and in whose eyes. once you look at each SEO campaign in that manner, you will more quickly understand what has to be done in each case and how to go about it.

I welcome you to SEO-highrankings and look forward to any comments and suggestions you might have to help us improve this site for you.

What Are The Most Crucial Digital Marketing Trends For 2022?

The realm of digital marketing changes every year. And, these changes are pretty notable during a specific year. Suppose you are a small business entity requiring constant updates on SEO, email marketing, and social media campaigns. In that case, you can always expect something new that could influence your digital marketing strategy. Before we move forward into trends of 2022, let's take a quick recap of trends in 2021. In 2021, Google has made changes in its algorithm. It has released its core web vitals ranking factors, and they are being update...

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What Are The Most Crucial Digital Marketing Trends For 2022?

Work at home on your internet home business
so you can stay home to be with your love ones.
Earn money online with a legitimate,
free to join, computer based,
Internet Home Business!