The online advertising world or the SEM industry is very compact yet a complex one. Search advertising or search engine marketing as some would prefer to call it, are being mainstreamed in myriad ways with the use of artificial intelligence (AI) and machine learning algorithms. And these changes have a significant, if not a critical influence on how you approach your search advertising.
Without a contention, Google AdWords and Facebook Ads take the major chunk of the search engine marketing market. In this post, we will look at how AI has influenced both these platforms, where they are headed, and how you can make the most of your campaigns, given that every business likes to get more out of the advertising buck.
Google AdWords – Getting more value
Google has been slowly incorporating AI into its AdWords framework as a result of which there is a greater scope of opportunities. They could be getting one up on the competition, or saving time for strategic thinking by automating low-level tasks. Let us look at a few ways in which you can make more from your AdWords campaigns.
Weeding out poor performing ads
The first scenario, clicks rolling in but no sales or conversions is a disastrous scenario for any campaign. This means you are leaking money without any ROI.
The second scenario, getting bids on an advert but not clicks, your quality score [QS] goes for a toss. End of the day, your ROI takes the fall.
Imagine the time taken to filter out these ads, analyze them and pausing them. If you are running a campaign for your business, it is easy, but in a scenario where you are handling multiple accounts, you will be spending all your time here without any time to create strategy.
How about using a machine learning [ML] algorithm to weed out these ads and pause them automatically? This will help in keeping your ROI intact as well as take care of QS.
Getting into the finer detail, your ML algorithm should be able to:
Abandon or pause the ad before it affects the ROI. Based on previous performance factors, it should be able to estimate potential gains and losses using statistical inference.
Analyze at a molecular level. The ML algorithm should be able to factor in other individual segments like mobile traffic, non-revenue producing browsers, times and days that see a poor performance and ad variations before it pauses the entire ad outright. With this analysis, it can close or fine-tune the non-performing factors one after another with realtime analysis.
“Automation and machine learning are a big emphasis on Google currently and our industry as a whole. The more we as practitioners can leverage these tools, the more time we can dedicate to higher-level strategy and other account growth opportunities.” – Josh Brisco, Sr. Manager, Retail Search Operations @ CPC Strategy
Using dynamic ads as a part of your SEM strategy
Dynamic search ads are an ML-based tool offered by Google AdWords as a part of the platform. These ads generate automatic headlines that can capture the attention of the searcher. All you need to do, is to create and upload the list of landing pages that you want to generate dynamic ads for. The tool will identify searches that it deems fit for your landing pages and generate ad content using the phrases from your landing pages. Sounds easy, but imagine doing it manually, if you are running multiple campaigns.
Using ML, AdWords also generates ad suggestions. Ignore them at your peril because these are generated using prior performance data. Incorporating them after due diligence will boost your results.
Dynamic ads can also be created using a custom ML algorithm that should incorporate:
External factors such as days and times.
Mix and match the audience, imagery and copy with multivariate testing using self-learning or evolutionary algorithms.
Used with due diligence, they could save your ROI and time.
Using automated bidding for best results
Using machine learning algorithms to cap your bidding, is becoming popular today. Bidding is a very important mechanism in search engine marketing – keeping your bids low means losing out on opportunities, and keeping them high means an ROI sacrifice.
Google Adwords comes with an automated bidding interface, however, it lacks the intelligence of maximizing your ROI. Maximizing ROI would require the input of certain external factors like seasonality, consumer trends, demographics, purchase behavior, and customer lifetime value amongst others.
A good ML algorithm for automated bidding must:
Be able to estimate the price range of each ad based on previous bids.
Calculate and factor in the click value from each click depending on the previous click data. For this, it should factor in the website data and this is a challenge. If you have multiple landing pages and keep removing or adding new ones, previous data that is fed to the algorithm could be bad or zero. Therefore, use the algorithm for aged landing pages only.
Identify the bidding landscape changes and results and adapt quickly to them instead of assuming that past performance guarantees future performance. This could be a big challenge for want of niche data.
Make use of existing platforms
What we discussed above could lead to an assumption that a custom ML algorithm is a necessity. However, we are speaking about marketing and hiring data scientists would be a waste of money and time when there are a platforms that could be leveraged to do the needful. Let us look at some:
Trapica: The best part of this tool is that it can scale your campaigns by identifying the right audiences and matching them to creatives thus optimizing bidding.
Acquisio: Built for Bing, AdWords, and Facebook ads, this ML platform helps you cut CPC and CPA while raising clicks and conversions.
Frank: Works with Facebook ads and AdWords and connects to millions of publishers. Frank is automated to launch campaigns and optimizes them by channel, creative and target audience.
Cognitiv: This tool uses deep learning and predicts the best spends using customization based on historic data for each brand, based on historical data.
Google has already announced its “AI-first” future when Sundar Pichai highlighted their efforts of expanding and integrating AI and ML capabilities across their products, 2 years ago.
Apart from the Google AdWords platform, choosing an alternative to create and control spending could be a challenge, however, knowing your requirements well and comparing it with the features of your chosen platform, will be a wise way to go about it.
Facebook ads – Improving campaign performance
Unlike Google, Facebook has a lot more relevant data about users. The recent scandals, albeit negative, are evidence to this fact. Concerns over private and personal data are not misplaced. Commerzbank and Mozilla have taken a negative stand over security concerns.
However, this goldmine of data that Facebook has, used with security and in a proper manner can result in much better insights about user preferences, tastes, and behavior. This will also help run relevant and personalized campaigns that can get better results, additionally, users can breathe easy without the generic ad bombardment every time they log in.
This filtered data is used by Facebook to help marketers create ad campaigns and the platform churns out a host of automated optimization options, helping marketers run effective ad campaigns.
Let us look at Facebook’s ML capabilities that can help you achieve this.
The importance of campaign objectives
The best part of the Facebook ad manager is that it wants you to specify a campaign objective, unlike any other platforms. Most other platforms give you objectives that are not specific to a simple goal. For example, one ad campaign cannot raise brand awareness, get you more reach or traffic and still get you a good ROI. One campaign for one objective is what works.
First up, while creating a campaign, you must understand what is to be achieved. The ad manager gives you thirteen options to choose from. Remember, campaign objective is not a cosmetic attribute. It will define the reach and placement of your ad. For example, if you choose “video views, Facebook’s AI algorithm will place the ad in front of people where there is a better chance of viewing, derived from user behavior.
Once chosen, the campaign objective cannot be changed post-launch. If I was doing it for my business, I would choose “conversions” and choose the sub-objective higher up as a CTA. This will help me keep my campaign, unique amongst all those ads looking for clicks.
Criticality of placement
Facebook looks at making money and this is the reason why most campaigns have placements offered this way. The more the ad serve, the more money Facebook makes, however, for marketers, choosing all placements will result in placement optimization through Facebooks’s AI algorithm. It is a win-win situation.
When chosen, the algorithm will decide where to place your ads considering the lowest CPM (Cost per thousand impressions). Placement optimization can save up to 20% costs when “Facebook newsfeed” and right-hand column are selected manually.
There are strategies that you can create using add-ons like Instant Articles, In-Stream and FAN, but brand safety becomes a concern there. Though there are filters available to categorize the placement, the newsfeed is a better choice considering the brand. A small price to pay, but worth it.
Optimizing ad delivery
If using campaign objectives was one part of the delivery mechanism, you still have options to further customize “Optimize for ad delivery”
Here, you will see options depending on the campaign objective you chose, and you can further focus on building a user persona to deliver those ads. “Value” is the latest addition to the list of choices.
AI Marketing is the future and has already turned into a mainstream feature in the search engine marketing or the PPC space. Micromanaging keywords and bids is no more a marketer’s job, it can be taken care of by simple algorithms, while strategy takes the center-stage for marketing success. Many industries are yet to include automation into their marketing and the first players to adopt AI/ML technology will see a quick boost.
Over 2.4 billion people across the globe and about 70% Americans use social media and it is critical that businesses leverage this channel with best marketing practices to shore up their bottom-lines. Be it marketing, support or sales, social media has become a big weapon in the marketing arsenal. It is an invaluable asset in terms of customers interacting with the brand and vice-versa. With millions of tweets, likes, and interactions being generated by the minute, it is impossible for big brands to keep up with the data flow. Human intervention in the form of employees takes the front seat, however, even the biggest of brands have at best, “tiny” social media teams. This is where AI SMM or Artificial intelligence-based social media marketing comes in. The situation today is – a business that ignores the capabilities of AI SMM loses out on a multitude of opportunities.
Automation is the only answer to the deluge of data that is growing by the day. But automation has its limitations and so does a human brain. Crunching huge amounts of data is not a human specialty and talking and interacting with humans is not a strong point of automation, at least not yet. Humans have to prioritize on data crunched by automation software (AI SMM) to create engagement opportunities, so the entire situation becomes symbiotic, where one part is human intellect and the other is artificial intelligence. Let us look at some areas in which AI can transform social media marketing for magical results. This is what we term as AI SMM.
1. The complement of human intelligence and AI SMM
AI applications and human beings form a complementary team in a social media marketing or SMM process. AI is growing leaps and bounds through extensive research in terms of natural language processing. However, real-time and targeted engagement remains a challenge. Whereas, human beings, on the other hand, are adept at engagement while they fail at crunching massive amounts of data that AI can achieve in seconds. This complementary relationship between AI and the human brain can be put to use effectively when deployed with a well-thought out strategy. AI SMM, fine-tuned, is also capable of removing noise and deliver useful data to an SMM marketer, so that he can be effective and quick in his approach to engage and convert.
Chatbots are not only used on website frontends but have also found use in the social media marketing niche. Chatbots are evolving quickly and today they are used to handle smaller customer issues while the bigger ones are delegated to human intervention. This translates to effective use of human potential. Chatbots are equipped to create and handle multiple conversations at the same time and are available 24/7. This, I have already discussed in one of my previous blog posts – AI-Based Marketing – 12 winsome AI ideas to leapfrog your efforts.
The fact that over 60% of customers expect an answer to their complaints in 60 minutes or less is a reality. By deploying chatbots on customer support platforms, they can help keep customers happy and improve retention rates. Not that chatbots will resolve all queries, but they can keep a customer engaged while flagging humans for faster resolution of issues. Chatbots can also prioritize complaints and help boost social media engagement by better customer interaction.
3. Post intelligence
Artificial intelligence is capable of identifying engagement opportunities on social media. A business called post intelligence has developed an application called PI that can track social trends in a given niche. The tracking data is then matched to the user’s recent posts and level of engagements thus creating an opportunity to fine-tune or recommend content that can be posted. It also has the capability of generating social media posts. As a social media marketer, you can imagine the possibilities here.
Pinterest has acquired a business called Kosei to add to its AI capabilities and predict personalized recommendations for users depending on their interests and search data. Kosei uses a recommendation modeling algorithm to help Pinterest churn out relevant results.
Bright is a job search business acquired by LinkedIn in 2014. Bright used machine learning to match employment opportunities with candidates. The bright algorithm helps LinkedIn to assess hiring patterns, work experience, locational preferences, and other myriad data to score candidates for a given employer. LinkedIn adds a new dimension to its job opportunities section by integrating Bright in addition to its data making it a more focussed hiring portal.
6. Slack bots
Slack bots throw guesswork out of the window for social media marketers. This AI SMM tool helps them to develop effective posts to promote their brands more effectively while suggesting content. Slack bots are seeing deployment in content marketing too since they are adept at analyzing niche content and suggesting the next steps. In the case of SMM, they analyze the posts on specific social media platforms based on the suggested niche. Slack bots can also predict engagement success rates by comparing your posts to others, especially the promoted ones. In short, they help create effective and focussed social media campaigns by taking out the guesswork.
On of the best AI, SMM technologies have been deployed by Facebook to engage and enhance customer interaction. Facial recognition saves time on tagging on the Facebook platform. It is still in the early times, but with facial recognition history, Facebook may use the data to deploy the algorithm to suggest products, offers, and places.
8. Marketing Automation using text mining
AI’s machine learning technology is enabling text mining and it will be very helpful for marketing automation techniques. Text mining algorithms are meant to analyze both, structured as well as unstructured data, analyze, and predict customer behavior trends. In turn, this will help marketing automation in terms of hyper-personalization which is lacks in today’s marketing strategies. It can also predict the correct times for social media posting, and will help reach a diverse audience to create maximum impact of social media marketing campaigns.
There are many tools like Buffer, HootSuite, and Co-schedule that can help you automate social media marketing by scheduling posts for a month or more, depending on your SMM strategy. So, what will take weeks can be achieved in a coupled of hours. However, they will not help with interactions or engagements, and human interaction is necessary.
There are many AI solutions out there, but there is no holistic solution that can serve the purpose. It is necessary to choose wisely and ensure that your choices add value to business. They should be deployed to extract holistic, actionable intelligence for the business and not as a solution to a subset of a marketing process. In the case of social media, they should be capable of uncovering insights and should help build customer-centric social media marketing strategy. Using social media automation tools creatively is the secret sauce that CMO’s need to figure out.
For more help on creating an effective AI-based social media strategy, get in touch with us today.
Google updated its search engine algorithm on 6th of June 2019. And, now there is a chatter about an unconfirmed update on July 11/12th 2019. Result – the whole SEO community is shaken and stirred. Some lost traffic, while some gained and as an SEO professional, you must be running pillar to post to find out more and rectify, especially if your or client’s traffic dived southwards. Is AI SEO, the answer to your woes?
Let’s look at it at a deeper level. With all due respect to every professional’s knowledge and skills, there is every reason bother about search engine updates. Taken that, you have been honest, built a technically fantastic website (as per technical SEO recommendations) and marketed it organically without using or focussing on bad links or using copyrighted content. Only the market or consumer trends will effect your traffic and nothing else.
I have been following the updates just for the sake of
profession and never made unnecessary changes to any of mine or client’s
websites, apart from making them customer centric and none of them have been
hit, over the last 15 years. There is a secret to it, of course. September
2013, the Hummingbird update was what got me going.
You, me and SEO
Following AI SEO
techniques to create an SEO strategy is a good idea, once and for all. I can
understand that everyone is in a hurry to promote keywords and get to the top
of Google’s organic results. What I do not understand is, if you you are not
better than the one on the top, how do you expect to get there.
Following success and getting one-up is the game here, and
not gaming the search engines. If you are trying to game them, surely, you need
to think about damage control with every update. Search engine updates are here
to create a level playing field and playing by the rules is the only way to get
AI or artificial intelligence “was” for the nerds. Today, it
is effecting every facet of your digital life – Alexa, Siri, AdWords, FB ads,
Amazon or Netflix recommendations, you name it and it’s there. So, it’s already
made headways into digital marketing, so, what’s wrong with applying it to SEO.
AI SEO – The impact
and the relationship
What do you think the search engine algorithms are? They
understand more than we can perceive including irrelevant backlinks, keyword
stuffing, bad content etc. They rank your webpages depending on these and many
other factors and, are created to learn using machine learning which is an
integral part of AI.
Understanding AI and playing by the rules is critical to
success. This can help you create cohesive strategies and bring more bang for
the buck. Let us see, in this post, how you can leverage AI SEO for better ROI.
Today, the impact of AI is very strong. For example, the
search results on Google that you see, take into account a number of
considerations like favorite websites, geographical location, search history
and similar customers who searched the same query. This means that the impact
of AI on page rankings will be strong and can vary very quickly due to customer
behavior. Your SEO strategy has to consider this impact with a critical eye.
Role of Machine
Learning in search engine rankings
SEO or search engine optimization is an organic marketing
processes executed to tame search engines and get to the top of organic
rankings. Of course, marketing is ever-evolving (which keeps me interested in
the first place), and search engines also evolve at the same pace, especially
in the area of SERP or page rankings where they exercise utmost influence.
As SEO professionals, we have been meeting the algorithm requirements through keyword optimization, metadata, acquiring inbound links and adding new website content frequently. Did we forget something? Will get to it in a minute.
The leader of search engines, Google continuously improves
search results based on search trends and not by what you and me do. Google is
consumer specific and analyzes search trends over time using machine learning
and applies the same to its algorithms. How many of us SEO professionals have
tuned the search to consumers? We have always ranted ranking and ranking and
So if traffic falls for some websites and rises for some
after an algorithm update as a result of an organic fall, don’t fret, you just
need to adjust your sails to the search engine winds. If you had the consumer
in mind, the adjustment will be small, but if you had rankings in sight, it
could still be your best fall ever.
Google estimates that 50% of search volumes will come
through voice in an interactive language, by 2020. And, Google is ready with
its voice assistant, image search and maps locations, bettering it by the day
to interpret natural language and provide relevant results. Are you working
towards it? Is your SEO working towards
using natural language keywords?
Applying AI is the only way to understand and tame the
search engines. There are many tools out there, like Moz, Yoast etc. that can
help you with keyword usage, optimize content and page optimizations. However, tuning your website to rank for
voice search is the the key to success.
Content is critical to SEO and we are not talking content
marketing here. We are talking about shape, size and tone of content that needs
to change effectively. AI can help you create opportunities to reach wider
audience. However, it is for you to intertwine these opportunities and create a
proper and sustainable SEO strategy.
You could, but how? Every secret lies in the data. Check
your content, blog posts and other publications for traffic data and analyze
why some did well and some did not. How many of them appeared in voice search
and what did you get out of them? An AI
empowered digital marketing agency could help you do well here.
AI helps you leverage consumer insights and create
strategies around it. Kia Motors did this successfully by partnering with an
influencer marketplace to find the right influencers. And, do you know how the
marketplace found them? Using AI. Kia’s 2016 Super Bowl commercial is a perfect
example of attracting relevant consumer groups for their Optima model, using
AI used in content can provide insights and ideas about:
Landing pages – performance of old ones and
suggest new ones.
Personalized content – dynamic content depending
on user preferences.
Experiences – Unique to customers according to
Additionally, tools like BuzzSumo or Hubspot are able to pin
point customer preferences in real time enabling you to act in time to win
business. There are many other AI tools out there that can help you leverage
your content for best use. As an SEO professional, you can well understand the criticality
of having those above in your arsenal.
– AI to the rescue
The best way to attract or captivate a visitor to convert is
through hyper personalization. IF the messaging is fine tuned to the language
used by the visitor, messaging at times he/she prefers and using names is the
best way to further your interests. I
mean, wear the visitor’s shoes and you will understand what I am talking about.
Standing out amidst the impersonal content that rules the
internet is the only way to get to to the visitor’s heart. In fact, data says
that about 80% businesses achieved revenue targets and more using a proper
personalization strategy. AI based personalization that is customer intent
based can actually raise potential profits by about 15%. Personalization
engines created using AI will see a rise and obviously adding personalization
to your website, content and SEO will see hyper results.
Another great example of personalization success is
Starbucks, which offers loyalty cards by leveraging mobile app data. This
enables the business to provided menu recommendations on mobiles to customers
approaching the store. Their secret to customer success, despite having 90+
million transactions a week along with a lot of data. That’s what leveraging
data using AI for hyper personalization, can do for your business.
The future of AI in
Search engines like Google evolve continuously and as SEO’s
we cannot expect ourselves to know what’s on the inside of a search engine
algorithm. It’s only when the updates are deployed, we measure the results,
happily or unhappily. Sad, but true.
However, realising that all those changes are
customer-centric and keeping the customer in mind is of utmost importance. If search engines are leveraging AI to meet
consumer needs, why can’t you do the same to cater to search engine needs.
AI based tools are adept at measuring how your blog post or content will
perform in search. Isn’t it a great starting point to better your marketing,
with AI SEO?
In short, AI has matured from a data collection and an analytics
tool to become an integral part of digital marketing. The sooner your business
realizes the impact of AI SEO to your marketing bottom-line, the better. The
bottomline is that your SEO has to evolve alongwith AI and that you will nomt
be able to do without the use of AI. Deploy and see results.
Artificial Intelligence or AI is what it is – artificial. A software that can learn from enormous amounts of data that it is fed. AI has been an ambiguous concept until recently, and no marketer wanted it to touch it with a bargepole, or make it a part of his digital marketing strategy or learn/ implement “AI marketing”.
2019 is seeing a paradigm shift in AI usage owing to clarity and capabilities that have been proven to work, and marketers are more than willing to incorporate it into their marketing strategies.
AI, as I can see, will keep evolving for the next 25 to 30 years. In this piece, let’s discuss the uses of AI in digital marketing to make it more relevant and effective – AI marketing. Before we get there, let us look at a couple of important facts.
According to a MeMSQL survey on 1600+ marketers, it was found that over 61% wanted to incorporate artificial intelligence and machine learning, as they will be the top data initiatives in 2019.
Salesforce says that most marketers believe that the use of AI will grow over 53% in 2019, which is more than any other technology presently in use.
The internet has turned into a huge repository of information collected at an alarming rate through logins, behavioral trends, subscriptions lists, IP addresses, web crawls, and many other processes. This information when processed through an AI capable software, to make it more meaningful, to analyze, becomes very useful to all stakeholders including marketers.
The best example of
such deployment is Google AdWords or Facebook Ads that deliver “relevant” ads
to the sites you visit or on your Facebook page. That is AI in action, and for
marketers, it is a giant leap forward since “relevance” results in more clicks
and thus more bang for the buck, in addition to making the advertising process
The most potent weapons in the AI arsenal are deep learning, machine learning, and natural language processing. These weapons are a marketers dream when deployed for a focussed purpose.
Every marketer works with data or information about customers or prospects. When that information gets analyzed to create logical and usable inference through segmentation or lead scoring, it becomes highly useful. Now let’s take the dive into those winsome dozen AI applications that can help you market better.
Search has revolutionarily changed over the years
and has slowly become a bigger challenge for marketers in terms of search engine optimization
and how marketers create and market their content. This is the result of AI
taking over, and most important deployments that have contributed this are
Google’s RankBrain and voice search.
Prime examples of voice search are Amazon’s Echo, Google’s Home devices in addition to Microsoft’s Cortana and Apple’s Siri. These have a simplified search where simply pressing a button and using your voice gives you desired results.
According to a Google blog, about 70% searches that Google Assistant handles are in conversational and natural language. People do not use keywords to search through voice as they do in a classic Google search.
This has become a huge challenge for SEO. Classic keywords and the long-tail ones go out of the window, and the use of conversational keywords has risen. So content now becomes a conversation instead of being monotonous, well-written or informative. Creating a balance between these factors is a huge challenge for content marketing.
2. Search Engine Marketing
As I had mentioned above, search engine marketing is probably the most benefitted by the use of AI technology. Digital advertising has come a long way in predicting and delivering relevant advertisements to users on both, the Google AdWords platforms as well as Facebook Ads.
Data collected from search [Google] and interests [Facebook] and a combination of both is processed through AI for demographic as well as personalized information collected over time, analyzed and used in a focussed manner to deliver those advertisements. In fact, today there are many third-party AI platforms like AdText that are evolving to serve the purpose more effectively.
Across the globe, major brands and websites have
begun to converse with visitors and customers through third-party apps like
Facebook Messenger, WhatsApp or Slack. The delivery of messages and replies
becomes faster instead of waiting on phone-calls.
Today, many websites have followed suit and offer Chatbots on their website frontend to understand and process visitor queries. These Chatbots are AI-powered and most of them are capable of understanding and responding to open questions asked in vocal language.
Chatbots comes with
some major advantages – saves on human time, they are available 24/7 and retain
data. Another great advantage is that they can handle multiple queries at the
same time, so a customer or visitor need not wait on an IVR forever.
One of the best
examples of Chatbot implementation is Sephora. It uses a beautiful
Chatbot to offer excellent cosmetic products, based on some great beauty
advice. With the Sephora Visual Artist, one can test cosmetics like
eye-shadows and lipsticks. It is capable of identifying facial features and
uses augmented reality technology [AR] to apply the chosen product on a user’s photograph.
This Chatbot actually mimics a sales representative. It cannot get any better,
Chatbots are self-learning tools that are not expensive to create.
4. Creating and Generating Content
Yes, creating content is no more a challenge, of
course, none of the AI tools are perfect enough to do that. Human intervention
and editing is inevitable.
An AI cannot write about politics or happening news or even a blog post. However, it is capable of creating content useful for a website. No wonder then Forbes, Associated Press and other brands like The New York Times, CBS, BBC, Washington Post, and Reuters is making the most of its limited capabilities. They mostly put it to use to create and write reports using available data.
There are a few intelligent tools like Quill, Wordsmith, and Articoolo amongst many others that are being used by the above-mentioned brands.
If you follow the Washington Post, you will find hundreds of articles in there are credited with Heliograf – an artificial intelligence technology, used by them.
5. Content Curation
AI may not be able to generate content perfectly, but
it can curate it accurately to show relevant content to visitors and customers.
Content curation using AI is normally used for personalized content recommendations. A typical example is “people who buy X also buy Y,” as we consistently see on Amazon. Another fantastic example is the Netflix recommendation system that suggests movies and TV shows that could interest you.
You can see that both the recommendation engines are pretty accurate.
6. Email Marketing
Personalization is the key to email marketing. And by
personalization, I do not mean something as primitive as mail-merge to change
names, addresses or greetings, it is at a much deeper level and helps establish
the right connect with a customer or visitor.
This also involves
machine learning technology that analyses tonnes of data and concludes the right
date and time to deliver the email, the frequency of emails that a recipient
prefers the kind of content that he/she likes the most.
AI into email marketing can get you more clicks and thus more business.
Tools like Phrasee, Boomtrain, and Persado are a few tools that can help you integrate AI into your email marketing campaigns.
7. User Experience
UX or User Experience is one of the most sought after factors for conversions through a website. AI empowers marketers to personalize website experience. Of course, this involves insights into terabytes of data that may include devices, location, demographics, interactions, etc. The end product or UX can be customized according to the results.
A good UX results in repeated visits to the site and improves the chances of conversion. For example, Chatbots are a great medium to enhance UX and interact with the visitor.
8. Web Design
Web design no more depends on the programmers or a designer. Today, you can design and deploy a wonderful website using tools like Grid. It uses AI to create a website in no time using inputs like text, CTA’s and images. This actually saves on price, time as well as resources. If you are looking to migrate to the cloud or have not already embraced cloud computing, you may have to positively think towards putting your website on a cloud hosting platform for best performance.
9. Speech recognition
AI-powered, voice-activated devices are flooding the markets all around us. And, these are a challenge for marketers because these devices understand most dialects and are very accurate, and it is overtly difficult to get into voice-activated search results.
AI-powered natural language processing algorithms have grown to be over 95% accurate and Baidu claims an accuracy rate of 97%. Using AI, these devices today, are able to interpret requests correctly and provide the required information with accuracy.
10. Audience Segmentation
As we spoke about personalization above, the need to segment the market data is of prime importance before applying AI to it. The more granular the segmentation, the better the personalization and marketers have to realize that this seemingly unimportant task until now, has taken the front seat to get better results from their efforts.
In fact, AI is also adept at segmentation
and targeting, if you can set your standards accurately and apply them to the
AI. Deeper the standards, better will be your segmentation. Complex
segmentation also involves AI at the level of sentiment analysis to create
People are changing, so is your competition, which means, sticking to static segmentation is not going to work anymore. Dynamic segmentation involves AI and behavioral analysis becomes critical to better segmentation.
Let us say, I at 50, want to buy a gift for a 7-year-old, a static segmentation may not be the right choice, while a dynamic one will put me in the right segment depending on real-time data and behavioral analysis. Better segmentation results in better targeting and the results are obvious.
11. Augmented Reality
Augmented Reality or AR is an outcome of computer
vision which a process of programming computers to ‘see’. And the computer
would collect and process the videos and digital images that it captures from
Absolutely perfect computer vision programming involves huge data sets of data processed through machine learning. This results in training a machine, robot or a computer to identify or recognize objects.
Accuracy of computer vision is
critical to developing a good AR and its applications in marketing. AR is a
layer over computer vision and is highly dependent on it for AR to work
For marketers, this empowers them with AR advertising that can integrate with the target’s environment without being intrusive. AR can open up new avenues of marketing like offers, product insights, shopping, etc. in a highly effective and powerful manner.
AR is already being used by a few furniture, beauty, and home improvement businesses like Home Depot, Lowe’s, Ikea, L’Oreal, Sephora (as discussed above in Chatbots ), Estee Lauder, Lenskart, etc.
12. Predictive Analysis
Predictive analysis is the use of statistical algorithms and machine learning over huge data sets of data to predict future conclusions and the probability of buying or selling.
There are innumerable uses for predictive analysis and resulting models as you can see. However, in the case of marketing, predictive models can be used to determine if a specific visitor will convert or not, or how many visits will it take for him to convert, etc.
The criticality of predictive analysis is that it highly dependent on the data you feed it. Like most marketers who have tons of outdated data, will not be able to make proper use of predictive analysis. The probable mistakes in your data or the data that is no good for the present market will give you useless models.
The best marketing example of predictive analysis is the way you rank or lead-score your prospects. A predictive analysis applied to such data can give you insights like who could be a “qualified client”. Acting on such information becomes much easier for sales with focussed priorities.
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AI Marketing is where the future is. The benefits of better decision making have always been valuable learning for all of us marketers. AI helps you make better decisions about your digital marketing strategy. Choosing a modernistic, AI integrated digital marketing agency is the best way ahead for your business instead of replacing teams to learn any new marketing initiatives.
In the posts that follow, we will look at how AI-based marketing can help your efforts in SEO, SEM, SMM, and other areas, individually.