4 months ago on
What Impact AI could bring in Storytelling
An AI based robot is creating sensations by flaunting humanistic expressions, picking her favorite bollywood star and giving her opinions on women empowerment, businesses such as banking, insurance etc.
Yes that’s Sophia for you, world’s most advanced robot created by Dr. David Hanson of Hanson robotics.
The concept of artificial intelligence is age old, but has been in vogue, since the past decade as smart technology started ruling humans.
But how will these machines know what we want?
Will they get better than us with creativity over time and eliminate the need of humans like it happened due to mechanization during the industrial revolution?
Let us sit back and analyze if AI is capable of changing the game to the extent of driving human storytellers to the edge of extinction.
Man Vs Machine
The one important thing that distinguishes humans from cyborgs is that we feel and we respond with emotions. And more than that we can convey those emotions to others with equal intensity and make them feel the same way. That is the power of storytelling that we possess.
Human mental network is complex with a lot of patterns left unexplained. So there is a long way for us to go before we think about incorporating these emotions in machines.
But as vehement as this argument gets, the fact that artificial intelligence has been evolving cannot be denied. Several experiments carried by techies of the most renowned institutes have given clearance to the fact that machines are successful in empirically reading human reflexes and understanding the emotional arcs.
Machines calculate the Visual valence induced in audience by a certain scene or piece of content. It is evident from this fact that they will evolve and eventually aid in storytelling business.
In attempts of fine tuning AI systems the scientists have grabbed inputs from human responses to motion graphics and what specific elements have triggered a positive or negative response and their emotions.
AI could work alongside humans in the process of storytelling. If humans write a video script, AI could adorn the script with its own inputs of background score and visuals.
It would be like a generator to charge the human storytelling mode.
The system is known to continuously learn from its experiences.
Pitching in AI in the scripting process will hugely influence how content is discovered, created, conveyed and consumed.
Identifying potential concepts
The way content is moulded changes each day. Stories are generated as a result of observations. These observations emerge from triggers and trend patterns. Computers and software are capable of detecting minor deviations from normal patterns and are quick and efficient. It also gets rid of subjectivity.
The human brain tends to get biased towards stories that seem acceptable to the observer. Machines on the other hand rules out subjectivity and brings up a valid and an all round significant content.
The information doing rounds of any topic invokes perceptions in human brain to identify and comprehend. Machines do not get sidetracked and lack other reviewing obstacles which have led them to transcend humans.
What would take humans ages to analyze ,interpret and organize, machines can do it with the blink of an eye. We can only imagine how lives of many professionals working with large amounts of data will be simplified with AI coming into use. With the data sorting being automated, humans can focus and invest more in storytelling
A writer’s biggest fear today is that AI taking over the human race with its ability of content generation.
Big publications are already using algorithms for generating narratives and news.
Researching topics and keywords, apt media and references, formatting are steps in creating interesting articles.
Platforms such as Wordsmith are being used by The Associated Press to generate financial reports with data input.
Quill is a natural language generation software which replicates the input to meaningful statements by analyzing the objectives of the story.
Heliograf is the in-house scripting software used by the Washington Post to publish articles.
NLG platforms have been used for generating short reports on sports, election alerts in the U.S. and tweets.
A machine’s neural system is confined to what its creator has fed it while human creativity is limitless.
According to the MIT’s Associate professor Iyad Rahwan “Human authors have nothing to fear at the moment, but if we can build machines that understand the very essence of human experience, we would have bigger problems than simply losing jobs in creative writing,”.
But that is still a long shot owing to the unbeknownst mysteries of the neural functioning.
Pan it across the media
We live in a world where the word “viral” no longer instigates panic. It only incites curiosity. The media does not control how content flows anymore. It is the giants of social media who do.
Facebook,Twitter, Instagram own classified algorithms which determine which content occupies their user feeds. Search engines decide what content should be retrieved for the user based on the patterns of his search.
Rather than stressing over the fact that AI might outshine the human race in the story telling business why not contemplate and incorporate machine learning in the content discovery.
Automation would bring about exceptional transformation in storytelling right from tracing target audience for a story to reverse mapping the audience psychographics to find out what story would intrigue them.
Given the fact that, the one size fits all theory does not work with the audience today, the giants of the digital world have started using data driven approaches to target audience.
News organizations have adopted the idea of headline testing which involves generating multiple title versions for a piece of content or article. The testing is carried out with an A/B testing tool which splits the traffic reaching the website and finds an optimize title based on performance metrics.
Extrapolating this idea, machine learning can be deployed to determine article or title length, expanse and position of the visuals etc based on the device on which the content will be retrieved the most.
Scientists will stop at nothing to make AI the ubiquitous element of technology in near future.
So it is wise for us to give up on the narcissism and embrace the apparent future-the progressive idea of content creation which is the humans and humanoids mulling things together.
Let’s Wrap It Up
The human nuance and data powered intuition are capable of creating path-breaking stories if used the right way. Just imagine a sci-fi story created with point blank tech details and aesthetic emotional arcs as a result of the man-machine alliance.
The human subtlety and mechanical calculations are quintessential to each. And maybe far in future machines will surpass the creator.
There is no reason to look at emergence of AI as a peril to human storytellers. The advent of AI will only revolutionize the concept of storytelling.
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5 months ago on
How AI and Machine Learning Will Shape the Future of SEO
Since the inception of Search Engine Optimisation (SEO), it has been going through various transformations. It is evident that Artificial Intelligence (AI) and machine learning is going to change SEO soon.
AI is a system which is constantly evolving and changing. Nowadays, SEO prioritizes more on content, links and user experiences.
It is a form of artificial intelligence. Machine learning gives the opportunity to computers to learn without being programmed.
That means software programs will be able to change and grow accordingly when exposed to new data. This will make computers more adaptable to new data.
Machine learning is not a new concept. Even in 1990s, basic machine learning algorithms existed but with minimal usage of applying it.
From recently only, Google started making use of it in its searches and we started seeing rapid changes whenever there are new major updates.
RankBrain is Google’s new game changing algorithm introduced in conjunction with Hummingbird. It was introduced to help in identifying and interpreting the intent of the content and showing result pages which don’t include the words users searched for; but contains information related to the category or idea of the query.
RankBrain is designed in such a way to continuously determine and integrate new features on its own. Even though, you may not have noticed any major changes in searching; RankBrain is definitely doing an outstanding job.
On the billions of searches Google process everyday, 15% of those enquiries had never been processed before. From 2016, Google uses RankBrain to process each of them; where its resources are used to learn how to investigate all kind of queries including the rare ones.
To analyze how AI and machine learning will shape the future of SEO, we need to study about the history and current scenarios of SEO. Let’s take a look at those:
How SEO evolved?
When SEO started, it was very easy to rank top in a search engine as the results were based on keywords used. If you wanted a top position in search results, all you needed to do was use the phrase suitable for your title and the content and you are done! You were guaranteed one of the top most positions in search results.
The basic idea was that the number of times the keyword used was more on your page; your ranking will be higher.
But this also paved ways for some unethical search engine optimisation practices by various companies such as hiding keywords in the background of websites or putting keywords off screen.
Different types of tactics were developed for ranking high on search engine which led Google to change the algorithms used.
As Google had enough with the unethical SEO practices, Penguin 1.0 was introduced by Google on April 2012. It was developed to block various web spam tacticssuch as duplicate contents, stuffing of keywords, link schemes and also unwanted redirects.
Based on Google’s quality guidelines, Penguin decreased those sites’ ranking where it felt has violated the guidelines.
Current scenario of SEO
Various algorithms used by Google have helped a lot in kicking out spam filled sites. Also this scenario forced marketers to create high quality contents to get into search results.
In the past, if the SEO techniques were based on keywords; at present, it’s based on technical SEO, link building and speed of the page.
In the past, technical SEO only makes sure whether you use suitable keyword, but now it also focuses more on creating greater user experiences.
Now it includes various factors such as user behaviour, page speed and responsiveness of mobile pages.
Now Google focuses more on quality content rather than keyword stuffed contents. Engaging on high quality content will always decrease the ranking of low quality content even if it has high keyword density.
Future of SEO
The future of SEO will mostly rely on artificial intelligence rather than relying on a formula to create organic search result listing.
AI will be relying on machine learning, big data and user experience. Using AI and machine learning, search engines can learn from user behaviours and will be able to provide a list of contents users will most likely search for.
The following are the trends that are more likely to shape the future of SEO:
In 2015, Google has introduced RankBrain into its search algorithm. As said before, it has made keyword phrases irrelevant.
RankBrain is the third most important ranking factor in their search algorithms.
- Understanding user intent
It will play an important part in ranking as major part of search results are based on artificial intelligence. Now, when marketers are thinking of creating content for their website, they need to think more than just keywords to hit the ranking on the search engine results page.
They also need to think what users will hope to find on your web page when they click from the results on search engines.
Marketers should be vigilant to get clues from search intent from their queries. There are four types of queries based on the user intent:
- Navigational: A user looking for a specific information on a specific website
- Informational: A user trying to get some information to read
- Transactional: User trying to pay a bill, creating a new account or even trying to subscribe newsletters
- Commercial: A user wishes to purchase or trying to get information to purchase later
- Schema Markups
It is code or semantic vocabulary that you create on your webpage which helps the search engines to have a better understanding of your content.
This in turn enables search engines to give informative and accurate results for the users. It looks like Google will be making use of new schema markup supports for carousels, data feeds, job listings etc.
Impact of AI and machine learning in the future of SEO
Emergence of machine learning and artificial intelligence will definitely bright up the future of search engine optimization. In favour of SEO, AI not only delivers useful content to users but also makes sure of what fits to user’s need.
Rather than sending users to a page that has more likely content, machine learning AI system will send users to the page that not only answer their initial queries but also can answer follow up queries.
It is very evident that AI and machine learning are definitely going to revolutionize SEO in delivering a greater user experience.
So don’t even think of compromising the quality of content on your website because no one wants to get listed last on the search engine ranking.
If you are not sure in creating content that will hit the top rankings in SEO, you can definitely outsource them. Our team is happy to help you with. Learn more about our products and services.
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6 months ago on
How AI Can Improve Your PPC Campaigns
If you have ever invested in Pay Per Click or PPC advertising in Google or Facebook, you know that it can take up lot of your time and concentration. Setting up big budget ad campaigns and continuous monitoring of performance and budget is a full time job in itself.
As you may know, many of repetitive tasks can now be done by machines without any human intervention. Marker’s tasks such as email sending, impression counting and conversion tracking have all been automated in the recent past. This is also true for PPC campaigns. Machine learning and artificial intelligence are already monitoring and fine-tuning paid ads.
In this blog we will discuss how AI is improving PPC campaigns and also look at what the future of PPC campaigns look like.
How can AI Improve your PPC Campaigns?
- Dynamic ads
Marketers put in a lot of effort in writing the perfect ad copy for their target market. Wouldn’t it be great if the ad changed itself to suit the person viewing it? It’s not magic and many PPC platforms are already doing it.
Facebook Dynamic ads show different products to different users based on their interest and browsing history. Dynamic Search Ads in Google Adwords generates ads that match user search with the products available on your site. This means that you don’t have to worry about missing out keywords. Google uses AI to learn about your website and serves up exactly what users are searching.
- Ad delivery Optimization
Delivery of your ad to the right people at the right time can make or break your PPC campaign. Facebook ad optimization shows your ad to the right people depending on your ad objective set. For example, if your objective is website traffic, Facebook will show your ad to people who are most likely to click on the link to your site.
- Automated Bidding
Wondering what bid would land you top spot in Google search? Set your campaign to automated bidding and let machine learning do the guesswork for you. Google automated bidding adjusts your bid to achieve any of the below objectives chosen by you:
- Increase Site Visits
- Top spot in Search Engine Results
- More visibility over other domains
- Get more conversions
This is free and convenient tool offered by Google. However, it does not meet the flexibility of manual bidding. Consider a case where you would want to apply automated bidding only to a high conversion keyword and not the rest. Automated bidding will not allow you this flexibility.
- Discover audience
Application of AI doesn’t always have to be in the PPC platform. Applying AI and machine learning on user searches and customers converted can also give insights into management of your PPC campaign.
Consider the case of Arteric, which is into cutting edge technology for healthcare companies. Analysis of 250,000 searches for a pharmaceutical company revealed an unexpected opportunity in Spanish language search volume. AI is good at discovering new opportunities which a human would easily miss. In fact it is impossible for us to look for every permutation and combination of possibility. On the other hand, AI can easily skim through large amounts of data and pull out unexpected opportunities for your ads.
- Uncover relevant keywords
AI can discover relevant keyword by the same method mentioned above. Data analysis of search terms reveals real-world conversational language in your industry. For example, analysis of search terms may reveal that people search for ‘ideas for Christmas Gifts’ instead of ‘buy Christmas Gifts’. This can help marketers in finding keywords with buyers’ intent and wasting money on non-performing keywords.
- Pause low-performing ads
Not all ads in you campaign perform the same. Some ads get more conversion than others because of the keywords, ad copy and landing page. Pausing or deleting low performing ads not only saves ad money from being wasted, it also boost your ad quality score (Quality rating assigned by Google Adwords to your ad).
Monitoring ad performance to delete low performing ads is a repetitive and time consuming process. This can be automated by using Adwords Scripts and API integrations.
Future of PPC Campaigns
PPC campaigns are far from being fully automated. Some of the functions such as optimized display and bidding rules can be set with free automated tool. Others can be automated using Adwords API and Scripts. However most of the tasks require humans to make sense of the data and take decisions.
As technology progresses we will see machine learning take up more tasks. Who knows, we might soon see a time where you simply input your goal and budget and the Adwords AI takes care of the rest.
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8 months ago on
How AI-Based Tools are Transforming Social Media Marketing
From interpreting lab results in healthcare industry to automatically controlling air conditioning temperature, artificial intelligence is changing the face of industries and businesses.
It is also simplifying jobs of marketers by providing tools to make sense of consumer data on social media.
Social media gave marketers a powerful way to reach out to their target audience. However, application of AI has made it possible to reach out to each individual user with personalized content. Here is how AI based tools are transforming social media today:
Artificially intelligent chatbots are common on social media. There are more than 1, 00,000 Facebook Messenger bots and they are here to stay as messaging is the preferred way of interaction for customers. Chatbots allow businesses to send auto-replies, personalized offers and even solve customer complaints.
More than 2 billion messages are exchanged between users and brands every month on Facebook messenger alone. Companies with AI powered Facebook messenger bots see increased user interaction and sales.
For example, Tommy Hillfiger saw a 3.5 times more conversion on messenger than any other digital channel during New York fashion week.
Even Twitter has launched many features this year to promote interaction of users with brand chatbots.
- Image Recognition
People share more than 3.25 billion photos a day on popular social media platforms! Brands can draw useful information about users, with so much visual data on social media.
Photos shared by followers can give marketers a peek into places they visit, products they use and how they interact with brands.
For example, an apparel brand can discover where their customers wear their products based on photos discovered on social media. Currently, there is no way to find out unless people tag the brand on a rare occasion.
A lot of information on buying behaviours, usage patterns and aspirational value can be found out by marketers only if they could read and discover images like text.
Thankfully AI is making this possible through image recognition technology. Using technologies like Google cloud vision companies can scan millions of images on social media to identify logos, products and objects.
This is similar to Facebook photos auto-tagging that you might be familiar with. With this AI tool marketers can listen to what customers are saying through pictures and videos.
Paid campaigns give the best ROI in digital marketing. Managing campaigns on multiple channel and deciding on best bid for keywords can get difficult at times. Usually campaigns are managed by in-house team or a PPC agency.
AI Tools like Albert and Frank use machine learning to manage paid ad campaign, analyze result and suggest most profitable platform for placing ads. This takes the guess work out of paid campaigns and ensures best return on investment.
- AI Content creation
Social media success is dependent on good content. According to Gartner, 20% of all business content will be authored by machines by 2018.
There are already intelligent programs that can write financial summaries and fact based articles. Many of the tech giants are working on bots that can speak and interact like human.
Microsoft’s artificially intelligent chatbot ‘Tay’ was made live on Twitter to learn from other users and tweet like a human teenage girl.
Although the controversial account had to be shut down after it tweeted inappropriate remarks, Tay showed us that days when bots produce social media content are not far.
As Natural Language Processing develops, machines will be able to write human like social media posts to engage followers. They would also collect real-time data on trending topics and write interesting content that drives engagement on social media. A tool called Rocco has already done this.
Rocco is an AI powered social media marketing assistant that suggests fresh social media content likely to drive engagement among your followers.
- Customer Intelligence
Posts shared on social media platform can give useful information on customers. Marketers no more have to interrupt customers for surveys and conduct focus groups.
AI machines can search social media platforms for data that matters and collate actionable insights.
Converseon is already doing this by applying machine learning to voice-of customer data.
These insights can be used for market segmentation, building customer profiles and competitive analysis.
AI based tools are going to change how we consume information on social media platforms. This is the reason all of the tech giants and social media companies are investing heavily in it.
Facebook has a dedicated AI research team called Facebook Artificial Intelligence Researchers (FAIR). In 2014 LinkedIn bought Bright, an AI based job search portal, to better its job matching capabilities.
Pinterest on the other hand acquired a data software company, Kosei, to boost pin and product recommendations. It is only a matter of time before marketers start using AI based tools widely on these sites.
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9 months ago on
How Artificial Intelligence is Transforming the Customer Experience in Ecommerce
Have you noticed the relevant product recommendations by Amazon or the interesting movie suggestions by Netflix ? This is not a coincidence but the work of Artificial Intelligence systems supporting ecommerce sites.
Artificial Intelligence or AI is being put to use by tech giants as well as by smaller players across all industries. AI application is changing everything from gaming experience to security systems.
Ecommerce is also undergoing transformation as AI is enriching customers’ experience while shopping online. In fact, a study by Business Insider estimated that as much as 85% of the customer interactions will be managed without a human by 2020.
This is made possible because of the big data collected on customers from various sources. Combining high processing capability and machine learning by computers allows AI to learn about customers and give a human touch to shopping online. AI can take on the roles of salesperson, inventory manager, marketing and store manager!
AI is bringing back the experience of a salesperson helping you out in a brick and mortar store. Human like virtual assistant can recommend products based on your past purchases and your customer profile. A detailed database gathered about each user allows assistants to give hyper personalized experience.
Virtual assistants can also suggest on the right clothing based on your location, weather or suggest a suitable phone according to your day–to-day usage. For example, a virtual assistant may help you to choose the right type of boot for your dress.
This is done by searching the web for information on fashion and boots. The assistant visits fashion blogs, looks at Pinterest images and gathers data on similar shoppers to suggest the best pair of boots. Your assistant will continuously learn about you and your interest to come up with relevant product recommendations.
Companies are also working on voice recognizing assistants that can have a conversation with shoppers. Soon it would be possible to tell your personal AI powered assistant what you want rather than searching for the right keyword for your product. Natural language programming enabled AI systems will be intuitive and understand the context of interaction like a human.
Ecommerce stores have had to choose their layout, branding and product assortment that would appeal to their target until now. This will soon change as machines learn about you to give you a personalized store altogether.
People of different countries may prefer a different layout and feel of the store. Similarly, different age demographics may have different expectation from ecommerce sites. Baby boomers may be more likely to buy a product bought by their friends whereas millennials may prefer to wait until prices drop.
AI allows online stores to change their layout, offers, and branding to fit the customer. This is done by customizing smart banners, smart pages and smart elements that adapt to the customer visiting your site. This is like walking into a store custom built for you.
Artificial Intelligence will also help to identify counterfeit and duplicate products. Chicago based start-up 3PM Marketplace Solution is working on an algorithm that identifies counterfeit products. The algorithm uses pointers such as fake reviews, customer reviews and data from other marketplaces to spot a duplicate product.
Removing deceiving third party sellers will build trust and credibility for sites using AI.
According to Conversica, one third of the leads are never followed up with. AI can reduce missed leads by automating follow up messages and remarketing to visitors who browsed for considerable amount of time.
AI can be used for pre-sales marketing too. This is already done by many sites by remarketing the products that a customer abandoned in shopping cart. AI can target a customer who visited and follow them in all social media channels to show the exact same ad. For example, searching for mobile phones will trigger the AI powered remarketing to show your smartphone advertisements on all social media channels and display ads.
Using machines to learn and improve also allows a lot of marketing work to be automated. Companies are currently automating marketing tasks such as mailing, lead conversion and answering objections of prospects.
AI is also helping at the back end of ecommerce stores. The usual business intelligence systems fall short in inventory management and assortment management in today’s dynamic marketplace. AI can forecast demand trends based on predictive analysis in these cases.
Many factors such as competitors pricing, velocity of orders, supply and demand, seasonal popularity affect the demand of a product. By using AI to estimate stock required the store can avoid being out of stock or over-stoking on products that won’t sell in future.
After Sales Service
The role of marketing does not end at sale. After-sales service is important to get repeat business. AI is helping personalize after-sales service by automated feedback forms, timely mailers and renewal/replacement alerts.
Some brands are even connecting to intelligent appliances and send service alerts or fix problems remotely. For example, AI powered service system at Bosch can detect service issues with its dryers and washers and notify customers.
Being in continuous contact with customers ensure share of mind and brand loyalty.
AI enabled ecommerce sites are able to process data that is impossible for a human to comprehend. This gives the opportunity to gather data on the bigger picture for strategic decisions and yet act on a granular level to give a personalized experience to customers. AI is changing how customers browse, shop and experience ecommerce for the better.