data analytics


What: Meltwater’s Ana Hoyos, Latcom’s Valentin Bueno, and WeWork’s Ana Cristina Rivadeneyra discussed how they are using data and technology to build market share in Latin America at Portada Miami’s key insights panel: Marketing Tech in Latin America: The Opportunities Ahead.
Why it matters: Excellent data is essential for creating content that connects with consumers in LATAM, and brands shouldn’t shy away from partnering with technology providers to reach their goals in the region, according to speakers at participating in the panel on marketing technology in Latin America.

It’s “harder to get data in Latin America,” and even more difficult to build, according to Latcom CEO Valentin Bueno, a speaker at Portada Miami’s panel Marketing Tech in Latin America: The Opportunities Ahead. “We need to create our own data. The work is to build the data with the client. There is no one size fits all,” he told #portadaMIA attendees.

Using the right technology is also key, according to Ana Hoyos, Director of Meltwater Latin America, and also a speaker on the panel. She told attendees that brands shouldn’t be afraid of finding the right technology partners when marketing in the region.

You really need some sort of tool, and you need to use technology to help you leverage all of the data that is out there.

“There is a lot of data, so using the right technology and not being afraid to partner with the people that can give you the actionable insight,” is very important, Hoyos emphasized.

WeWork entered the region just two years ago, and panel speaker Ana Cristina Rivadeneyra, senior marketing lead at WeWork, said WeWork has developed its own listening tool to better understand WeWork’s customers in the market. The data gathered is used, in part, to determine the architecture and construction of WeWork’s work spaces in the region.

Partnering and Organization

Panel moderator Alejandro Clabiorne CEO of PHD Latam asked the panel participants to discuss their organizational approach to task of leveraging data and technology to reach consumers in the region.

“There are no barriers between tech and marketing,” at WeWork, Rivadeneyra said.

Meltwater places a lot of focus on AI, and works with companies that can help it “integrate data science into our daily operations,” said Hoyos. It’s important to educate customers who use Meltwater’s media monitoring and analysis services about the importance of data measurement and analytics, she said.

“Everyone needs to adapt. Everyone is on the boat,” so we want our clients to know “you don’t want to be left behind,” she told the #PortadaMIA attendees.

Latcom takes a partnership approach with its clients in the region to build data and systems than can guide its customers’ business decisions and planning, according to Bueno.


Technology and Data Insights

(L to R) Ana Cristina Rivadeneyra, Ana Hoyos, Valentin Bueno, and Alejandro Clabiorne.

When helping Microsoft launch out-of-home advertising, Latcom relied on technology to understand consumers’ behavior, Bueno said. After reaching a full understanding of the complex ecosystem of devices used by consumers in Latin America, content was tailored to fit those devices—which is often the mobile phone.

“Technology challenges everyone. We chose a complex task: how to use data to reach audiences that are difficult to reach,” Bueno explained.

Meltwater helps its customer Santander, the international banking brand, monitor its reputation in Latin America, said Hoyos.

“We create analytics that give them trends and insight. There is so much data. You really need some sort of tool, and you need to use technology to help you leverage all of the data that is out there,” Hoyos said.

Using the right technology and not being afraid to partner with the people that can give you actionable insight is very important.

“The most important thing for Santander is to understand the perception of its brand using data from traditional news and social channels,” Hoyos explained.

Meltwater uses AI and data science to track three million documents daily and organize the information to make sense out of it.

“What we have done is focus a lot on AI and companies that can help us integrate data science into our operations,” she said.

What: Block chain technology offers brands the opportunity to collect customer data and incentivize their behavior directly and transparently.
Why it matters: Customers can protect their personal data and monetize it, entering into a one-on-one relationship with brands through a technology called “smart contracts”. Smart contracts allow users to enter into data sharing agreements with brands that are “securely stored on the block chain along with the detailed terms and conditions.”

Block chain technology is poised to revolutionize how brands gather customers’ data and incentivize their behavior. The digital computer code that is best known for being used to create the crypto-currency known as “Bitcoin,” also allows for “smart contracts,” whereby two entities (i.e. a brand and a customer) can enter into agreements that are transparent, verifiable, secure and direct.

So what do “smart contracts” mean for brands?

Smart contracts backed by block chain technology have the potential to shatter the traditional paradigm whereby brands purchase customer data from third parties like Facebook, or loyalty programs that rely on consumer subscriptions but don’t provide a lot of purchasing behavior or product preferences information.

Enter Killi, a consumer application available on iOS or Android. Killi lets consumers sell their personal data directly to brands and receive compensation every time marketers choose to buy it.

Using block chain technology, Killi collects users’ locations and their purchasing data which is stored on the user’s device. Brands can then purchase the data with the permission of the app users.

A personal data locker is controlled by the user and secured by the block chain. This allows you to take back control of your personal data from those who are selling it today without your consent.

When users authorize brands to access their data, Killi stores the payment on the Killi app until users choose to redeem it.

“Killi acts as a personal data locker that is controlled by the user and secured by the block chain. Killi allows you to take back control of your personal data from those who are selling it today without your consent,” Killi tells consumers on its website.

The Killi website is a bit vague on how the technology actually works, but “the offering of being able to monetize your own personal info does sound intriguing,” said Jay Gumbiner, vice president for Latin America at IDC.

“We could even imagine some consumers being worth much more than others based on their purchasing habits, socioeconomic placement, educational level, etc.”

We could even imagine some consumers being worth much more than others based on their purchasing habits, socioeconomic placement, educational level, etc.

“In terms of using block chain for maintaining the integrity of that data and being able to easily track who has been able to access the information, it seems like blockchain could be a great use case for managing data such as this,” Gumbiner noted.

The Killi app relies on block chain technology to create what is known as a “smart contract” between the app users and brands.

Smart contracts allow users to enter into data sharing agreements with brands that are “securely stored on the block chain along with the detailed terms and conditions,” according to Yves Benchimol, CEO at the French startup Occi.

Thanks to these smart contracts and encryption via the block chain, consumers can “easily request an exhaustive list of all retailers/brands they have shared data with, and in which conditions, in compliance with GDPR,” Benchimol said.

Occi is working on its own products for retailers that use block chain and smart contract technology to reward customers while providing a rich set of data about their shopping behavior to brands.

Smart contracts with consumers provide a channel for consumers to share their information with brands, while providing brands new possibilities for influencing consumers’ behavior.

Brands can “create a campaign rewarding a shopper for visiting a store and define the amount they’re willing to reward a shopper along with a total budget, which will be locked in a smart contract,” Benchimol said.

Retailers have access to well-established sources of data on consumers’ preferences and behaviors from a wide range of sources, but new laws such as GDPR create barriers to using that data without consent.

Block chain and smart contract technology “bring forth a new way to solicit data sharing from shoppers, that is more transparent and fair because it directly rewards them,” Benchimol said.

What: We talked to Mebrulin Francisco, managing partner and expert in multicultural marketing data analytics at Group M. She shared some of the key insights to take into account when approaching data analytics.
Why it matters: Using and understanding big amounts of data to understand consumers’ habits and needs lies at the very heart of success in marketing.

Portada: In your opinion, what were the biggest technological trends that impacted marketing data analytics in 2017? Where do you see them going this year?

Mebrulin Francisco, Managing Partner, GroupM: “Some of the biggest technological trends in 2017 impacted not only how marketing works but also how we behave as consumers. The top three that I can think of are Artificial Intelligence(AI)/Machine Learning, Internet of Things (IoT) and Augmented Reality/Virtual Reality (AR/VR). If the CES is any indication, we have not seen the last of these trends. In fact, some of the biggest product introductions came from this category, the Vive Pro and wireless promise to introduce wireless VR technology.

But here is what is going to be really interesting in 2018.  How are companies going to start connecting the data streams through all these devices and technologies? And how is that going to fuel artificial intelligence? To date, we mostly have been using artificial intelligence to automate the data mining process. But what happens when machines start collecting and connecting marketing data analytics from all these devices and learning behavior? We are not there yet, but we are seeing companies starting to play in this area.”

Impact of Claritas Acquisition

Portada: What’s your perspective on the Geoscape acquisition of Claritas in the context of multicultural research?

M.F.: “I personally think this is amazing for the industry. Claritas is a well-known and trusted partner in geolocation analysis. However, they didn’t have the level of rigor and audience depth that Geoscape had through their multicultural audience models. So when it came down to choosing a data partner with this level of geo/spatial range it was always between these two companies. However, Claritas usually won out given that Claritas is also connected to Nielsen data. Since it’s all rolled into one, I suspect that now Geoscape will have an increased level of visibility across the industry, with a higher chance of a broader appeal. I’m personally excited to see how these two powerhouses of local data will come together and create new product offerings to change the way we think about and use local data.”

Also from Portada: 6 Things You Need to Know About Geoscape’s Acquisition by Claritas

Important First Steps

Portada: Many companies are beginning to use data analytics, what are the first steps to get into data analysis?

M.F.: “If an organization is starting from scratch, the first step is definitely to hire talent that understands analytics and data infrastructure. Marketing data analytics can be very profitable and propel a brand’s competitive advantage. However, if you do not understand how to build a team of data scientists, how to use the appropriate tools or how to create a data platform that can be embedded into the culture of the organization, it would be very difficult to get much use out of it. The organization then needs to train key decision makers in the organization once it puts the practice of analytics in place. They need to train them on how to integrate analytics into their day to day work.”

The first step is definitely to hire talent that understands analytics and data infrastructure.

What to Do With Marketing Data Analytics

Portada: Once you have great amounts of data, how do you make sense of it? What questions should firms “ask” their data?

M.F.: “This is the opportunity to get creative. The fantastic thing about analytics is that you can ask what is happening. You can ask why it’s happening and will it happen again.  As a result, these questions can be applied to any discipline.

For example, working with brand marketers these are some of the questions I tend to ask. What was happening at a macro level that was causing a difference in consumption by multicultural segments versus non-multicultural segments? Do we have a true understanding of the life cycle of the category of multicultural segments? How was the brand consumed? Leveraging usage behavior, can we predict how many multicultural segments will be in the market for a given category? Can we predict the potential conversion pool for our brand? If so, can this be quantified to help the brand management team discuss appropriate media funding? Finally, what are the nuances of this category and brand that must be addressed to help the brand become more relevant for the customer?”

Recommended Marketing Data Analytics Tools

Portada: Which data analysis tools would you recommend?

M.F.: “This is a hard question to answer. It is because the tool you use is dependent on what you are trying to achieve. For example, if my end goal is to help my organization quickly decipher a pattern I might use a data visualization tool such as Tableau. This would be very different if what I wanted was to run predictive analytics which would require other tools that allow me to mine massive amount of data such as SAS, Oracle or IBM.”

Brands create a dangerous blind spot when they assume that the same strategic approach for general audiences should be applied to all consumers.

Portada: What would you say are the nuances of the Hispanic market to take into account in marketing data analytics?

M.F.: “Brands assume that the same strategic approach for general audiences should be applied to all consumers. As a result, that creates a dangerous blind spot. Ideally, brands should address this blind spot by leveraging data analytics to prescribe appropriate implementation processes. However, when brands apply a data-driven approach in a multicultural space they create challenges. They limit consumer ethnicity data in datasets; there is a lack of expertise to contextualize multicultural trends, and a myriad of cultural complexities can blur meaningful insights.”

Check out Mebrulin Francisco’s VIDEO interview:


What: Media intelligence and data analytics company Meltwater has acquired Cosmify, a knowledge discovery platform that uses advanced machine learning technology.
Why it matters: The fifth deal in Meltwater’s ongoing M&A streak adds machine-learning, data-science experts to in-house machine learning team.

Meltwater, a global leader in media intelligence and data analytics, announced the acquisition of Cosmify, a knowledge discovery platform that uses advanced machine learning technology for in-depth analysis of corporate data sets. Cosmify’s technology will help Meltwater’s industry-leading platform intelligently manage the vast amounts of data from multiple sources that businesses need to make competitive decisions based on insights from the outside.

With its fifth acquisition in less than nine months, Meltwater is quickly building on its impressive data science engine aimed at offering the most innovative and dynamic media intelligence platform in the world. With 55 offices throughout six continents, Meltwater employs more than 1,500 employees and 50 percent of Fortune 500 companies use its services to shape business decisions.

Cosmify founder Eugene Ciurana and chairman Bart Swanson launched their first machine learning company, Summly, with 16-year old founder and Oxford student Nick D’Aloisio, and sold it to Yahoo for $30 million in  2013. In 2014, the team, with co-founders Dr. Ana Nelson, Connor Goodwolf, and Sriram Krishnan, launched Cosmify. Bart Swanson of Horizons VenturesMuleSoft founder Ross Mason, and CA Technologies VP of Engineering Leonid Igolnik are part of the advisory board.

Now, after selling two companies in four years, the team is joining Meltwater’s push to build the largest AI-driven data repository in the world, giving companies a competitive edge by allowing them to leverage insights from  external data when making business decisions

“The best business decisions are based on forward-looking data. Today external data on the open internet is one of the most important sources for forward-looking information,” says Jorn Lyseggen, CEO and founder of Meltwater. “Cosmify’s advanced discovery, clustering, and classification capabilities will enhance Meltwater’s ability to connect the dots between a wide range of data types from internal and external data and ultimately help business leaders make more informed decisions.”

“95% of all data is unstructured and unwieldy, but it also contains a vast trove of unexploited value,” says Eugene Ciurana, CEO and Founder of Cosmify.  “Our unsupervised learning system extracts knowledge from internal and external, unstructured data sources like PDFs, free-text, spreadsheets, media files, presentations, cloud drives, calendars, or chat systems – most often hitting on valuable information nuggets that eluded the very users who produced them.”

“Cosmify’s knowledge discovery engine analyzes customers’ very large and dynamic data lakes to produce vectorized information, and when fed into our existing Data Science platform, automates generation of highly customized outside insights – all without having to import their internal data into our systems,” says Aditya Jami, Senior Director of Engineering & Head of AI at Meltwater.

The acquisition of Cosmify comes on the heels of several key acquisitions for Meltwater that have broadened its global footprint and cemented the company’s commitment to data science and machine learning. Meltwater recently announced its plans to acquire Canada’s Infomart, followed closely by Hong Kong-based social big data SaaS solution Klarity. Earlier this year, it acquired Oxford University spinout, Wrapidity, to add AI-based crawling to Meltwater’s platform and last year, Meltwater acquired Encore Alerts, a US-based data science driven media monitoring company.

Meltwater is actively seeking investment opportunities and partnerships to continue expanding its media intelligence services globally, with a strong emphasis on data science.

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