Author: Kotryna

Machine Learning & BlockChains: A Cutting Edge Innovation to Digital Advertising

Post contributed by:

Kotryna Gasiunaite, Product Manager – Emerging Technologies

 

Artificial intelligence (AI) is defined as intelligence that is portrayed by machines. AI enables machines to perform cognitive tasks that are typically done by humans. However, much of what we see in the sci-fi movies is what scientist have been exploring since the 1950s. No doubt, much innovation has happened within the sector of Machine Learning and Deep Learning, which are segments of AI. While much innovation has to continue while AI is able to debut itself fully within digital advertising, its early onset and testing is well underway. Similarly, blockchain protocol aims to improve the landscape by proving transparency and streamline the supply chain efficiency.

Today, there are thousands of brands that have used machine learning to provide better customer experiences. Marketers and advertisers have realized the potential of big data and machine learning algorithms as a tool for improving their campaigns’ effectiveness. Though some brands remain uncertain about the impact of artificial intelligence in the immediate future, the possibilities have started to fuel exploration and investments in several new ventures with the digital advertising industry. However, the technological and talent pool shortage has slowed down the progression beyond its current exploration phase.

AI: Automated content creation

Several companies are using natural language generation or NLG to tell their data-driven stories faster than normal human beings. Natural language generation uses human-designed algorithms to parse data as well as to convert it into readable copies. For instance, some e-commerce firms are using artificial intelligence to come up with product descriptions. Real estate agencies are also using AI to create property listings. That means these companies don’t have to struggle with writers that compromise the quality of their content. That’s because AI enables them to create automated, high quality content. Additionally, this technology is more cost-effective and it can be used by in-house advertisers and marketers to write descriptions instead of hiring freelancers.

Basically, NLG enables advertisers or marketers to use their data to automatically create content. This enables them to write many stories within minutes and use them to attract exponential traffic and generate more leads and increase sales for fewer or same resources.

Improved customer experience

Global spending on cognitive systems is expected to hit $31.3 billion by 2019. In fact, some experts say that artificial intelligence might double the rates of economic growth by 2035 while boosting labor productivity by up to 40%. Although there is the lure of the cost-savings that artificial intelligence brings to businesses, the major goal for advertisers and marketers is to ensure that their brand experience is more predictive and personalized. Perhaps, that’s because redesigning a digital experience or making over a site or an app is one thing and adding cognitive computing and thinking power into the embedded experiences is another.

Mona Lisa is Gravity4’s public face for artificial intelligence, similar to IBM’s Watson. It is a cloud-based cognitive engine for digital marketing platform, programmed with the capacity to thinking like a human media analyst. Mona Lisa uses machine learning and natural language processing to enable brands to have one-to-one, relevant consumer to brand experiences. The data harnessed and utilized is on the basis of product and new consumer insights.

MonaLisa: AI
Gravity4: AI & BlockChain

AdTech: BlockChain

For the past several years, adtech has been battling ad fraud ranging from: incorrect counting, ad viewability, discrepancies, just to name but a few venues. In EU, we have pending GDPR deadline fast approaching on top of that, to ensure brand ads are placed on safe sites. While AI will no doubt help with this, there are innovations that Gravity4 has been working on. Aside from the upcoming announcements from the Gravity4 Labs team, my team has been working on the blockchain as a venue to bring transparency to the digital marketing platform.

While some countries are still light years behind in the blockchain discovery, one study states, 14% of financial market institutions intend to implement full-scale, commercial blockchain-based services by this year, while adoption of 65% to follow by 2020. It is reassuring to see the FDA and IBM’s Watson Health explore not just the financial sectors for blockchains, but also within the health-care to construct an audit trail of all transactions on an unaltered distributed ledger for the patient data exchange. This will further ensure the accountability and transparency in finance & healthcare.

All in all, the upcoming innovations of Blockchain, AI, and machine automations will continue to influence how we live, communicate, and shop. These influences, therefore, are indispensable and an unavoidable part of the digital advertising’s future. As such, we at the helm of this industry have exciting opportunity ahead of us.  

Kotryna
My name is Kotryna (pronounced: Kat-rina). My focused responsibilities include management of the programmatic platform, DMP, Machine Learning developments and to oversee the Ad Operations for the EU offices. I also contribute to the product strategy, manage product roadmap and coordinate efforts to drive our overall revenue for the AI marketing cloud, Mona Lisa.

Rise of the Chatbots: Future of Conversations

Mona Lisa - Gravity4
Mona Lisa – AI powered Chatbots

Post Contributed by: Gravity4 Product Manager – Kotryna G. (Pronounced Kat-rina)

If you consider every click, swipe or tap, the average American touches their smartphone over 2,600 times a day. The total time spent on them is over four hours daily in 2017 and currently, the primary means for interacting with our digital devices is through the graphical user interface, which has been a staple of personal computing for decades. But that’s about to change with the coming rise of chatbots, which offer an even easier way to interface with technology-through language itself.  

The convenience, increased affordability and availability of smartphones has led to a huge increase in the number of apps that can assist in some way with the tasks and data we need every day. But as chatbots become more sophisticated, we will no longer need to interact with apps, or even a device, directly. It can all be accessed through verbal commands. Several companies are already finding huge success with chatbots.

Mona Lisa

Super-Bots

Currently, the most visible example is Amazon’s Alexa, which works with their Echo speakers. The capabilities of Alexa are impressive. She can respond to voice commands by allowing the user to control all connected devices without using an intermediary device, such as a phone. This is especially useful when Alexa is connected to all smart devices in a home. When integrated properly, this chatbot can adjust temperatures, light settings, play music, answer questions and even order food, among other things.

Aside from Alexa, many other companies are launching their own chatbot versions, some of which function like Alexa, in that they are basically a virtual assistant. Other examples of chatbots that are high-ranking in the sophistication of their artificial intelligence are Siri and Cortana. All of these have been recognized for their ability to mimic human conversation, and most are considered super bots, in that they can perform multiple functions.

Specialized chatbots that focus on specific purposes are also growing in popularity. There are currently task-specific chatbots that tackle a wide variety of needs, including weather information, travel updates, restaurant and entertainment information, and health-related information, and it is likely we will see a growth in the popularity of these types of chatbots in the coming years.

AI powered Chatbots
Mona Lisa – Artificial Intelligence Powered Chatbots

Gravity4 Chatbots

We released our own Pixels Asia chatbots, powered by Gravity4 AI, as custom build products for the brand ecommerce and health websites as the first respondent for customer service. These bots are emerging among the small businesses as well and no longer just used in the tech companies and large corporations.

At Gravity4, we are constructing AI powered bots that will serve as digital assistants with online ordering and payment, customer service for answering questions and completing basic customer interaction functions, advertising purposes such promoting sales and raising visibility, and even providing valuable analytics from the data they collect.

Being present across the 20+ countries, we have noticed a global emerging trend with the use for personal assistant chatbots across the business world. You may already be using some of these bots to schedule meetings, book travel and even order dinner. These AI powered chatbots are starting to simplify our life and decrease operational costs for many business owners. They also offer additional ways to interact with the company, which is a benefit for the customers.

Chatbot Best Practices

Audience: Before launching new bot experiences, brands should determine their target audiences. This requires full scope research on reach and carefully defining the bot’s precise vertical in terms of content and commerce of service. This exercise will enable brand’s development team to come up with effective criteria for their bot to operate in.

Selection: It is always good idea to focus on one particular service or product. After the initial learning, the knowledge base of the chatbot can be expanded slowly by feeding it with more relevant or important data over time.

UI: To ensure a better user experience, a chatbot should have a good user interface. Data analysis components should be seamless and the main should be to maintain two-way conversations with different audiences on a real time basis.

 

Kotryna
My name is Kotryna (pronounced: Kat-rina). My focused responsibilities include management of the programmatic platform, DMP, Machine Learning developments and to oversee the Ad Operations for the EU offices. I also contribute to the product strategy, manage product roadmap and coordinate efforts to drive our overall revenue for the AI marketing cloud, Mona Lisa.