Startups vs. Monoliths: Who Does Big Data Better?

startupsvsmonolithsAs advanced analytics continues to become more sophisticated, businesses across industries are realizing how much business value there is in turning data points into actionable insights. With demand for big data ever increasing, a host of startups have emerged alongside the Microsofts and IBMs of the world to help organizations integrate, understand and leverage big data insights.

When it comes to big data, many people have the perception that bigger is better. They want to use services provided by the biggest companies, with the perception that the large the organization, the more access they must have to data. Big companies have so much first party data, they must know much more about consumers, right?

It may seem counterintuitive, but this is simply not true. With so many different data points out there, certain points will be more valuable to you in some instances than in others. In order to create a comprehensive data set, even the monoliths need to purchase additional points in order to fill the gaps in their own data.

Consider this in another way – a surgeon could have the choice between a scalpel and a machete. But just because the machete is bigger, doesn’t mean it is more useful to the surgeon. He needs the right tool that will allow him to make small, anatomical dissections. Having the right data is similarly important, allowing companies to target and personalize at a more precise level.

The real differences between startups and monoliths when it comes to big data has nothing to do with accessibility – and everything to do with service. Qualities such as adaptability, time to market for innovations, ability to be prescriptive and access to quality resources within the company will distinguish smaller companies’ big data services from the monoliths.

 

Adaptability

Startups have a big advantage over larger companies when it comes to adaptability. Shifting strategies with big companies is much more difficult for the simple fact that they have a lot more layers of management and much longer approval processes. Clients are often made to work within the monolith’s existing products and frameworks. Startups are leaner by nature, meaning their products are often more adaptable to your own business compared to those offered by larger companies.

 

Time to Market

In the same vein, innovations can go to market much more quickly with a startup. With high volume, high variety data that comes in at a high velocity through real-time data streams, it is important for companies to be able to rapidly experiment with all sorts of combinations of data, and adjust the tools they’re using quickly to successfully predict trends, identify customers and push out promotions at the optimal time. Without the lengthy cycles of a large corporation, startups are much more flexible and capable of working with customers to get them what they need, when they need it. Meaning if your data conflicts with how you’re currently running a campaign, you can change tactics right then and there. If a new technology hits the market, or you need an integration that doesn’t already exist within the platform, a smaller company is nimbler, and likely able to turn it around for you quickly.

 

Prescriptive Ability

In addition to longer decision and go-to-market times, large companies can become entrenched in the traditional way of doing things, which affects their ability to administer prescriptive and innovative advice. With more invested in the status quo, they run the risk of becoming reluctant to invest in new technologies and methodologies that might require an overhaul of their current businesses. Startups are not hindered by deep roots within a particular product, meaning they’re willing to try innovative solutions – focused on figuring out what will deliver the best outcomes, rather than protecting their own heritage.

 

Access to Quality Resources

Who you decide to do business with determines what – and who – you get access to. Larger businesses often have procedures that prevents their executive management from engaging in close contact with their customers, delegating that responsibility to scores of account representatives instead. While there’s no harm in this, there’s no real benefit either. When working with a startup, customers have access to management (and expertise) much higher up in the food chain – sometimes all the way up to the CEO. Because of this, startups often develop much closer relationships with their customers and take a vested interest in making their data programs successful.

 

When it comes to big data, perceived “volume” of data doesn’t matter. What you DO with your data, and how a company works with you to accomplish it, is much more important than the size of the business you’re working with. The next time you consider leveraging big data, ask yourself: what data do I actually need, and how will I use it to benefit my business? That’s the key to mastering big data.

Alley Watch: This NYC Startup Just Raised $2M To Give You the Genie You Always Wished For

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With Big Data, humans have the greatest advantage in understanding consumers than ever before. But just because the data exists does no mean you know how to use it. That’s why we have Grey Jean Technologies, the company that uses AI to give you all the information you need to target customers at your fingertips. With its intense personalization functions, the company’s signature Genie runs all the numbers specifically for each person providing solutions for your marketing team and not just ‘best guesses’.

Today, we sit down with cofounder Cosmas Wong to discuss the company’s recent funding as well as the companies roots from Wall Street.

Who were your investors and how much did you raise?

Grey Jean’s funding came from angel investors and company management, and totaled $2 million. It was a seed round and was led by myself. I was also cofounder of my last company, ENSO Financial Management LLP (EFM), which was recently sold.

Tell us about your product or service.

Grey Jean Technologies is a personalization company that improves customer acquisition and sales across all retail channels. Our recommendation engine, Genie, is powered by artificial intelligence (AI) and provides the most accurate predictions of consumer purchase behavior. This enables retail marketers to target shoppers with contextually relevant messages that drive desired actions, such as a store visit or redemption of a special offer. Genie uses big data and AI technology to organize retail’s unstructured data sets to connect the right deals to the right customers.

What inspired you to start the company?

Having spent years leading big data efforts in the financial sector for some of the world’s largest hedge funds, I saw firsthand the power of big data when used correctly – and also how challenging it can be to harness effectively. We had to understand how to preserve the integrity of sensitive data and use it to the benefit of all customers. My co-founder, Craig Alberino, was working on Madison Ave with big agencies in retail and CPG digital at the time, and encountered the same issue – retailers were struggling to convert their data into something real, such as increased sales or lead gen. Combining efforts and applying our combined experiences to retail marketing was a natural fit for us.

How is it different?

To date, personalization has largely been based on geo-location and basic demographic information. It’s essentially unsolicited targeting – more of a “best guess” rather than personalization. Genie uses the most comprehensive set of data points, including unconventional data points like political preferences and lifestyle, to create consumer profiles that are truly unique to each shopper. This is all continually updated through our eight proprietary algorithms to adjust individual customer profiles in real time.

Another way Genie is different is that it focuses on using artificial intelligence to drive actions, rather than just delivering insights. We actually help retailers take an action with their customer, rather than just presenting their data in new ways and leaving them wondering what to do with it.

Genie focuses on the person in personalization.

What market you are targeting and how big is it?

Grey Jean targets retail marketers. According to Juniper Research, global digital retail marketing spend will double by 2020, reaching over $360B.

What’s your business model?

Genie is a SaaS model. We bring data from disparate sources into a data management platform (DMP) using modern technologies for rapid data processing, like Spark, on the back-end. Our AI-powered recommendation engine, Genie, finds and weights underlying correlations, and converts that data into usable information, allowing retailers to make decisions and take action in real time. Ultimately, it enables retailers to do more than they could do otherwise, even if they had thousands of staff members.

Are there any concerns about privacy when using your solution?

If there are concerns, there shouldn’t be. We are housing anonymized versions of customer data. The analogy we often use is baking a cake – you add the butter, the flour – a bunch of individual ingredients which are identifiable and which you own, but ultimately once the cake is baked you can’t get the butter or the flour back out.  They’re not butter or flour anymore.  We’re creating fingerprints and personas for individuals in order to deliver the tailored and personally valuable deals for consumers, but we’re anonymizing the data in order to do that, and the end product ceases to be identifiable from its original form.

What was the funding process like?

The process for us was actually fairly unconventional. I believe most people are used to the typical “friends and family” Seed or A round of funding for a business. We funded a project to dissect a broken market. Out of that funded project came our business plan. From that solid foundation, it was pretty obvious what we had, and we were in the enviable position of having too many interested parties.

What are the biggest challenges that you faced while raising capital?

Our biggest challenge has been articulating how we’re different and better than other marketing tools out there. Genie sits at the intersections of a laundry list of buzz words – personalization, artificial intelligence, big data, machine learning – and each solution provider is using these terms in different ways. We had to explain how our product is unique, and being able to show our incredible results played a big part in that.

What factors about your business led your investors to write the check?

Our investors have worked with us before, but what its really came down to for us were the results, which speak for themselves. We can predict the next likely purchase at the category level (e.g. pool supplies) with 72% accuracy. In other words, the customer profiles that Genie creates are used to target consumers with individual deals that are relevant to them with such a high level of accuracy, generating more conversions, redemptions, visit frequency, foot traffic, time in store, basket size and brand affinity than other solutions.

What are the milestones you plan to achieve in the next six months?

Since the launch, we are in a period of rapid growth from both a corporate and customer standpoint. In the next six months, we’re expecting to expand our staff and close deals with some of the marquee clients we’ve been talking to. It’s a very exciting time.

What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?

There is a lot of uncertainty on the horizon for the VC and private funding market over the next year, but opportunities exist for businesses that can show value. My advice would be to focus on the fundamentals of building your business – the product/market fit, onboarding clients and hiring the best people to fill key roles, and then building out a revenue plan. Even in tough markets, if you have a product, a team and customers, there will be investors interested in your business.

Where do you see the company going now over the near term?

In the near term, we plan to keep growing our sales and marketing efforts, and continuing our conversations with leading retailers. We’re in an interesting time where retailers see the value of AI-powered personalization, but haven’t figured out how to achieve it yet.  Genie is an effective tool that can get them there – it truly delivers on the promise of personalization.

What’s your favorite rooftop bar in NYC to unwind?

It depends on who we’re entertaining. I like the Empire Hotel. The Press Lounge is also fun, but gets pretty busy. The Gansevoort at Park is great for lunch or early afternoon cocktails as it’s close to our NoMad office.

 

 

Interview with Cosmas Wong originally posted at: http://www.alleywatch.com/2016/07/nyc-startup-just-raised-2m-give-genie-always-wished/