Understanding Artificial Intelligence Marketing: Approaches and Techniques

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What Is Artificial Intelligence Marketing?

In marketing, artificial intelligence (AI) is the process
of using data models, mathematics, and algorithms to generate insights that
marketers can use. Marketers use insights gained from AI to guide future
decisions on event spending, strategy, and content topics. AI also makes it
possible to measure and optimize marketing activities without human
intervention.

AI marketing uses both classical machine learning algorithms and neural network methods to analyze patterns in large volumes of customer and user data, such as purchases, web visits, clicks, and product usage. Insights are provided to marketers through dashboards, reports, and recommendations.

AI marketing can be used at all stages of the marketing
process:

  • Planning and strategy
  • Product personalization
  • Promotion
  • Performance and tracking

Marketers use artificial intelligence in one of two ways. One is to use an existing marketing technology software with artificial intelligence capabilities. The other is to use in-house or outsourced development resources to implement artificial intelligence algorithms and technologies specifically customized to their needs.

Why Is AI Marketing Important?

The recent CMO Survey reported that marketers are seeing an increase of 27 percent in active use of AI technology in their marketing programs and expect to see an increase of 59 percent in the usage of AI in the next few years.

A primary reason for the importance of AI marketing is
that the insights it provides can help marketers increase the effectiveness of
their campaigns and achieve a faster return on investment (ROI).

Another key reason is that in today’s digital economy,
personalization is critical to remaining competitive. Personalizing products
and online experiences at scale is difficult or sometimes infeasible, and AI is
particularly suited to this challenge.

Core Elements
of Artificial Intelligence Marketing

AI marketing solutions have a dual challenge.
On the one hand, they need to make use of Data Science techniques and advanced
algorithms to generate insights from existing datasets. On the other hand, they
need to be practical and easy for marketers to use in their day-to-day jobs.

Marketing AI solutions that meet these
challenges have three main components: big data, machine learning inference,
and integrated toolkits.

Big Data

AI solutions ingest big data from a variety of sources, such as customer relationship management (CRM) systems, web analytics, or third-party data providers. They can be trained to comb through the data to identify patterns or insights that can benefit marketing programs, much like a human analyst would.

AI training relies on thousands of real-world
examples, which the algorithm uses to build a cognitive model, which it can
then apply to new, unseen data points.

Machine
Learning Inference

Once an AI solution has ingested data and trained a model,
it enters the inference stage, in which it can identify trends and predict
customer reactions to various signals. AI can operate in real-time, providing
outputs such as the best ad to show a specific consumer or the parameters of an
offer that will cause a specific customer segment to buy.

AI can also analyze large datasets to identify details
important for marketers. For example, it can automatically extract a list of
customers who are likely to respond to a specific promotion or predict future
trends for a large number of products to help make a strategic decision about
marketing budgets.

Integrated
Toolkits

At the end of the day, even the smartest AI
system will not be usable if it is not integrated with a marketer’s existing
stack of workflows and toolkits. AI marketing solutions must be delivered as
toolsets that marketers can easily access and use.

In many cases, AI can be delivered as an
enhancement to existing tools — for example, a new panel on an existing
dashboard that delivers a new type of insights or a widget added to a CRM
system that provides AI-driven analysis of customer data.

Benefits of Artificial
Intelligence Marketing

Here are several ways AI marketing can help
marketers drive better results.

Increased
Marketing ROI

AI software can provide actionable insights in real-time. These insights are delivered to marketers, who can then decide how to utilize the information. AI platforms can also act on these insights, leveraging the information in real-time.

For example, AI can analyze ad placements and
optimize for high performance at the lowest cost. The software then
intelligently distributes funds across various channels, continuously
implementing intelligent budget allocation processes to improve marketing
ROI.  

Personalized
Content Delivery

AI systems can go beyond simple customer segmentation, analyzing the individual profile of each existing and potential customer. If regular audience analytics provides demographic information, hyper-personalized AI processes provide information about each individual.

eCommerce websites, for example, leverage AI
marketing processes to deliver personalized content tailored to the unique
tastes and needs of the user. Streaming services, like Netflix, use
hyper-personalization to provide personalized content suggestions to each user.

Improved
Campaign Reporting and Measurement

Aggregating and analyzing the large volumes of data
generated from today’s marketing activities can be difficult. Marketers can
find it challenging to create meaningful reports and prove the success of their
campaigns.

With AI-assisted dashboards, marketers can fully
understand the elements of the activity they are working on, identify
successful patterns, and adjust their activities accordingly to improve
results. AI can also be used to build smart reports that can help communicate
the value of marketing activity to management.

Artificial
Intelligence Marketing Methods

Here are a few practical ways AI can help marketers in
their day-to-day jobs.

Sales
Forecasting

Marketers can use AI to process and analyze data about
customer transactions and interactions. AI can analyze any type of data,
including unstructured data like phone calls, meetings, and emails. AI
marketing solutions can help predict the sales outcomes of different sales and
marketing activities.

Customer
Insights

Artificial intelligence marketing can help analyze
customer expectations. By analyzing consumer behavior, AI can predict which customers
need your products the most and when. Digital marketers can automatically
create profiles and segments and target them with personalized offers.

Personalized
Pricing

Artificial intelligence marketing can also help digital
marketers personalize prices to individual customers and situations. In this
strategy, retailers set product prices based on the needs of their audience.

One example is a ride-hailing application, in which the
cost of a ride is dynamically computed according to the current availability of
drivers and other transportation options in the area. Another example is an
eCommerce site in which prices can be automatically adjusted to current demand
on the website or in the industry in general.

Content
Creation

AI can be used to generate content. At this point in time, AI algorithms cannot replace human writers but can produce simple blog posts and news releases. Conversational AI is widely used to communicate with prospects online and answer common questions. Digital marketers can also use AI marketing solutions to analyze content performance and predict content topics that will be successful in the future.

Automated Ad
Targeting

Marketers can automate the advertising buying and selling
process, using data generated from cookies delivered to visitors of apps and
websites. Artificial intelligence is useful because it can effectively identify
and target a large number of very specific audiences. For example, Facebook Ads
uses AI to target and retarget customer ads and is able to automatically create
“lookalike” audiences that resemble a company’s current customers.

Conclusion

Artificial intelligence marketing is not a
futuristic concept — it is already deployed in the field and provides practical
tools that help marketers save time and gain new insights about customers and
campaigns.

Still, beyond the immediate benefits, we are
only scratching the surface of AI marketing. In the future, human-machine
collaboration will create new types of marketing activities and new marketing
roles.

Just like the digital age introduced the
digital marketer, the AI revolution will create new marketers savvy in Data Science
techniques, who can create and leverage AI algorithms to transform marketing
programs.

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