Kirill Rebrov tells us how Demografy’s non-invasive technology protects consumer privacy and provides businesses with private data regulation compliance.
First of all, how are you and your family doing in these COVID-19 times?
Kirill Rebrov: Like most people, my family and I were affected by COVID-19. Thankfully without consequences. 2020 has definitely changed our lives, as do the lives of all other people. It affected industries and ordinary people’s lives. But I look into the future with optimism. Any challenges bring opportunities.
Tell us about you, your career, and how you founded Demografy.
Kirill Rebrov: Demografy is a privacy-focused data marketing platform that uses machine learning to predict demographics from masked names. The idea behind getting demographics from names was initially very simple. The true value of protecting consumer privacy while fueling businesses with data at the same time appeared only later.
The idea was born while developing a customer sign-up form on one of the software projects. There was a “gender” field along with the first and last name. Nothing special. And this trivial task led to the thought like “it would be easier for users to enter only names and get the rest of the fields pre-filled.” Proof of concept of detecting gender by name was completed the same night. However, it was easy and was not new. The turning point between fun project and startup was a proof of concept of implementing age range prediction using only names as input. It required learning many things that were new to me and that were non-trivial.
It even seemed impossible at some point. Later I even became too obsessed with the idea that it was possible, which led to several sleepless caffeinated weeks. I was literally throwing spaghetti at the wall day and night. Eventually, it ended up with a working technology prototype and patent application.
How does Demografy innovate?
Kirill Rebrov: We’re closing the gap between companies’ hunger for customer data and consumer privacy. Demografy’s non-invasive technology protects consumer privacy and provides businesses with private data regulation compliance while getting vital marketing information. I see Demografy’s mission in redefining the data marketing industry, which is currently based on non-opt-in consumer data use and private data reselling.
Demografy, on the contrary, doesn’t rely on private data at all. It both makes data marketing consumer-friendly and democratizes data for small businesses which traditionally don’t have resources and technologies for more expensive and data-hungry AI solutions. Besides privacy, our technology has the advantages of 100% coverage and accuracy preview before purchase. While traditional data append services, which are based on consumer databases, have poor coverage and unknown accuracy.
How the coronavirus pandemic affects your business, and how are you coping?
Kirill Rebrov: We basically have launched during COVID-19. Not the best time for any business activities, especially if you’re a bootstrapping startup. It probably affected our marketing performance in a worse way. However, as I said, I see opportunities, not challenges. While it may seem that COVID-19 transformed only the B2C market in positive ways (raising demand for online services, etc.) while leaving B2B SaaS struggling, it’s not necessarily the case. These hard times added additional purpose for Demografy. As part of our mission, we want to help businesses reduce their marketing expenses via marketing automation. This is what Demografy essentially does – it provides businesses with automated customer data collection, eliminating the need for time-consuming, expensive, and inefficient manual data collection.
Some friends tried to convince me that a new B2B martech product is not the thing businesses are willing to pay for today. However, I believe that marketing, the backbone of any business, is essential for businesses today like never before. And products that help businesses reduce their marketing expenses are in special demand right now. For example, many companies are forced to lay off part of their staff, thus increasing the load on remaining employees. Particularly, this has caused a higher demand for customer support chatbots to reduce the support workload on humans. This is where Demografy can help businesses stay afloat – reduce the workload on manual customer data collection and segmentation. So that’s the new demand in the B2B market – martech products that help businesses automate and reduce their expenses.
Did you have to make difficult choices, and what are the lessons learned?
Kirill Rebrov: Fortunately, we’re small enough to make such choices related to the workforce. Though, such transformative times affected all aspects of our business – from R&D to marketing. It forces us to seek new approaches in value proposition and marketing campaigns as well as re-prioritize new features and product development. Probably, it can even force us to make a pivot. So the main lesson is to not be afraid to make a pivot. Be open to changes and adjustments, especially in rapidly changing markets.
What specific tools, software, and management skills are you using to navigate this crisis?
Kirill Rebrov: We rely on Google Workspace for our enterprise tools, Microsoft Azure for infrastructure, Atlassian for task management, and started actively thinking about CRM. Regarding our management skills, we all are still learning since we’re self-taught Jack of all trades. It’s hard, but it’s incredibly interesting and invaluable to learn many new things and skills. Starting as a software developer and diving into digital marketing and video creation (so please do not judge our explainer video strictly) is a priceless experience and entrepreneur privilege.
Who are your competitors? And how do you plan to stay in the game?
Kirill Rebrov: Our closest competition is data append services, data brokers, and all sorts of consumer data resellers like DataSift, Acxiom, AccurateAppend, Datafinder, etc. The key difference is that they sell private consumer data. Businesses usually provide them with personally identifiable information like addresses and full names of their customers so that they can match records of a particular person in their databases and return additional information about the person to the business. Such approaches are the root of many problems in the industry. First of all, is privacy, of course. Non-opt-in sharing of personal data with third parties is the number one reason for data breaches. For example, the largest data breach in history happened in 2003 when 1.6B of consumer records were stolen during the transmission of data to and from Acxiom clients. Many still remember the Facebook / Cambridge Analytica scandal. The list is long.
Demografy, on the contrary, doesn’t use private data in the loop at all. The data privacy landscape is changing rapidly, and businesses should be prepared to adjust their marketing strategy appropriately. The introduction of GDPR in 2018 directly prohibits or seriously limits businesses from sharing personal data with third parties. Offering a GDPR-compliant and completely privacy-safe way of getting consumer data is the first advantage to help us stay afloat, especially in data-regulated markets.
Another advantage is coverage. Traditional solutions require too much information to provide about customers. This already limits the number of records businesses can segment since not all businesses have information like customer address or full name, while other businesses simply cannot or are not willing to disclose such information to third parties. And even provided with the required information, many data append services have relatively low coverage of 50% or less for demographics. As a result, the overall coverage is low. Demografy uses machine learning instead and is able to provide 100% coverage while requiring as little as just a first name or a first name and a masked last name.
At the same time, the quality of data of traditional solutions is questionable. For example, the most accurate match input parameter for data append is the postal address. However, this attribute is not perfect since only 66.9% of mail is deliverable as addressed, and 10.1% of Americans move every year according to NCOA and US Census, respectively. As a result, outdated records on both the client and data provider’s side may lead to an inaccurate match. Moreover, both provided data and data in third-party databases of data append services may simply be erroneous. Another challenge with third-party databases is that the original data source is unknown.
Demografy’s accuracy is not perfect too since we’re machine learning technology. However, our predictive technology provides an accurate estimate before purchase, allowing a business to decide whether to purchase data or not. It even allows purchasing only a part of the data that meets data quality thresholds.
If you don’t mind coverage, accuracy, and privacy, the one thing they’re still beating us at, they can provide detailed data beyond basic demographics. However, we’re planning to roll out more indicators in the near future. At the same time, our key goal is not to provide businesses with all possible data at low coverage. Instead, our key goal is to provide basic data but with 100% coverage and predictable transparent accuracy, Not to mention privacy and private data regulation compliance.
Your final thoughts?
Kirill Rebrov: First of all, I’d like to say to all entrepreneurs that you must see opportunities, not challenges. Every challenge is a demand for something. And you can provide a supply to this demand. Even if your industry is unrelated to industries that are transformed in positive ways (like delivery or eCommerce), you can still come up with ideas for a pivot. And you shouldn’t be afraid to make a pivot. It’s hard to break and change what you already built, but sometimes it’s the only way to survive and save what you built. One of the best decisions I ever made, I made during extreme pressure and out of necessity.
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