Access to increased big data sources by sellers will enable more precise Consumer Intent predictions. Sellers that have those capabilities will continue to improve their competitive advantage.

Personal assistants like Amazon Echo can link voice search to product search. This will drastically change how consumers search for products and services, and instead of giving consumers list of results to choose from, voice search will eventually choose for them.

Consumer intent will be verified by emojis and emoticons. With Facebook putting new options instead of the traditional “like”, using emojis will provide a more accurate intent tracking.

Layering location and time of day on top of intent will open new worlds to technology. Combined, these are powerful sources about a customer’s mind set, task and role.

Bringing together disparate data sources to form a complete view of your customer will be key for leveraging machine learning and predicting consumer behavior. Every piece of data matters.

Sophisticated tracking, programmatic technology and advanced data solutions will help marketers to better target high intent customers at different touch points of the buying journey, delivering a truly personalised experience.

Object identification is now a commodity thanks to deep learning technology. The next revolution in image analysis will leverage multiple data inputs (images + surrounding meta data) to train AI models to identify the human elements behind visuals.

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  1. As companies have moved to the Internet, decoding the customer intent has become a lot easier and difficult all the same time. Unlike in a traditional store, a website has given the organisation to capture the customer’s partial interest over a product through his various click points. Consider Netflix for example, Netflix launched an instant streaming service in 2007, one year after the Netflix Prize began. Streaming has not only changed the way our members interact with the service, but also the type of data available to use in our algorithms. For DVDs our goal is to help people fill their queue with titles to receive in the mail over the coming days and weeks; selection is distant in time from viewing, people select carefully because exchanging a DVD for another takes more than a day, and we get no feedback during viewing. For streaming members are looking for something great to watch right now; they can sample a few videos before settling on one, they can consume several in one session, and we can observe viewing statistics such as whether a video was watched fully or only partially.Another big change was the move from a single website into hundreds of devices and it is now instantly available. All these hoards of information have made decoding the customer intent relevant and very important for sustainability of business for many organisations.

  2. I think companies using machine learning are not only collecting data what we see or desire to buy. But, also are tracking in real time, the movement of mouse pointer or finger tip on website, if they don’t they should.

    Since, as body movement gives tons of clues so does the movement of mouse pointer.

  3. Technological advancement has totally changed our world. It has given new ways of doing things more easily and efficiently. One of the areas which has seen a drastic change is E-Commerce shopping websites. With the consumers having the facility to easily get what they want at home it has a become a huge success. But with new things launched, its updates comes in queue after it.
    Now with the companies with their hands on huge data and analytics, the sellers have computed the consumer’s intents of buying, trends of shopping and many more things which has helped them to statistically plan their ways of selling.
    Moreover with technologies like Amazon Echo, its making consumers more comfortable to do things. Sellers are also depending on progressive learning of the patterns of shopping with the help of AI and using it to filter the results for the consumers differently.
    Companies like Facebook made it further easy to know the thoughts of the consumers by introducing the use of emoji’s or emoticons have tremendously helped the sellers know what consumers want and create their action plan accordingly.
    Its not too far but a day would come soon in the near future when everything would be controlled by the human voice and all the consumers will have the filtered and desired results when they search for something.

  4. I think on one hand consumer intent technology is changing the way how we shop on e-commerce websites, every organization is targeting the customers with their data driven results for the search made by customer, it would obviously help in personalize customer experience but on the other hand it will just open up everything about the consumers to the organization. To me it is a bit annoying to see the same product that i tries to buy on some e-commerce website pops up again and again on every other websites , although this would be profitable for the merchants but at what cost.
    So consumer intent technology is obviously a big step towards the personalized experience but this should be somehow be controlled how much information about the consumer is up for data analysis.

  5. No doubt that consumer intent technology will definitely help businesses in delivering more personalized consumer experiences.
    As a consumer i do want more personalized experience but not on the cost of my privacy and my personal life, with more personal data getting online consumers are getting bombarded by different personalized offers that blind them while purchasing or they constantly spam consumers inbox.
    What consumer intent technology can do is to come up with the solution where as a consumer is only suggested what he really needs and at the right time, not in between a movie as it happens now (pop ups). This could even save a lot of marketing money for businesses.

  6. The recent developments in Big Data Analytics and Artificial Intelligence has really made huge developments in understanding the consumer intent but i don’t think that can be understood only from the facebook likes and emoji’s as they have very different indications and also depends on the perspective of the user. In order to determine consumer intent, it is very important to find out what kind of hobbies and interests does a consumer have so this can be achieved by knowing what kind of societies and communities the consumer has joined and is involved with,what kinds of pages they like on facebook and the facebook groups they have joined and is actually active in it,also from the groups which have high number of membership in a social network.From these it becomes actually more clear what does a consumer think and what are the products that can help them fulfill their thoughts.This actually helps in finding out how many more people are there, who share the same thoughts and interests as well as this can help in building a better and stronger market by providing those goods which are appealing to the consumers. It will not only grow the e-commerce market but also provide high revenue by increasing the number of sales,by meeting the increasing demands of consumers.This method can also be used to develop all other markets and develop the local departmental store into a big supermarket with various branches spread across different cities.

  7. The 2000s was the era of search when the endeavor of Google was to produce same results for any search query no matter who was searching (Black, white, young, old, girl, boy, american, asian and so on). There was one search engine of google which was used by billions and produced results without any discrimination. The next challenge for companies like Google and the likes is to create billions of search engine each uniquely suited towards the need of individual user. So going forward, the search results for ‘Tea’ in google would be different for different users highly based on their preferences and the locations and time they are searching at.

  8. As quoted by Matt Ware, BeyondD , I totally agree and absolutely second that. Decoding consumer intent is useful as long as it goes with the buying journey.
    Answering how to decode personal intent using technological data? It is NOT that easy, getting a like or some favourite emojis on a post does not reflect the true intent or purchase of the product or a vote for a politician on the actual polling day. Someone might have liked the post on Facebook about the latest company’s offer. Let me highlight, it was NOT just the offer playing its own part but could be the text or picture which was used to describe that offer. So trying to decode the INTENT is not easy as long as marketers don’t study the individual buyer’s pattern and their individual buying journey making it into final sales conversion.
    No Doubt with all these data available these days, they have succeeded so far in understanding JUST the part of their consumer but we all should not forget that they are dealing with humans not machine.
    I guess it’s a long way before we could actually decode the real intent unless big data companies are ready to invest huge in studying the behavioural consumer patterns and try to understand their customers. We can NEVER GENERALIZE or DECODE THE REAL INTENT, we can only just understand part of it and then we actually need to put all the pieces together in order to solve this challenging puzzle.

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