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B&L

First Data Refinery

Chile
Market: Internet and IT, Artificial Intelligence
Stage of the project: Operating business

Date of last change: 22.11.2020
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Idea

From master data we clean, repopulate, homologate and validate all the information to increase your channels and systems.

Current Status

B&L has had strong growth in sales and number of customers in recent years, opening high-turnover operations in Peru, and starting relationships in Colombia and Mexico. We closed 2019 with a portfolio of more than 20 first-class clients, which additionally have operations in Perú and sales in México.
We have over 12 large Retail companies, 3 Agriculture and mining holding, with over 45 subsidiaries with 5 user avg per subsidiary 225 users.
We acquire clients through our sales structure (presales, sales and post sales) using inbound and outbound strategies, this sum to our partner ecosystems all over Latin America that creates leads and work as resellers.

Market

Our target market are all companies which produce at least 6.000 critical data records (master data, customer databases, etc) a year and have an annual revenue of over USD $3M.

If we consider only the retail industry and focus on product data, on average a company handles 3.2 million rotating SKUs a year and has a yearly revenue of USD $1Bn in ecommerce. Taking into account our average ticket price of USD $4.2 per record and the total e-commerce revenue in Latam of USD $64Bn, then our minimum target market size is of 205 million records or USD $861M. If we extrapolate this to full retail (not only e-commerce), then the market size grows to USD $12Bn (taking into consideration Latam retail revenue of USD 900Bn).

In general, our solution is aimed to any company with an information system (ERP, CMS, MDM, etc.) trying to adopt a digital strategy in order to apply good data practices and reduce operational expenses or losses caused by carry-over errors in their data.

Problem or Opportunity

Latam e-commerce sales amounted to USD $64B in 2019, with a return rate of nearly 16% caused directly or indirectly by incorrect product data. Companies like Falabella or Liverpool lose around 11% of their net sales (USD $1.13B) a year due to dirty data.

Gartner has estimated that poor data quality costs organizations an average of USD $13.3M a year, affecting labor productivity as much as 20%. 20-30% of operational expenses can be directly related to bad data. Harvard Business Review has estimated that by adopting good data practices, companies could realize a 70% increase in revenue.

With corporate data growing at a rate of 40% a year, trying to fix this issue using human resources alone has proven to be unsustainable.

Solution (product or service)

We offer an AI-driven solution to standardize and enrich corporate data. Our proprietary algorithms allow us to extract information using technologies such as image recognition, web scraping and document understanding and use it as aggregated data to fix and enrich our clients corporate data. Our key strength is our vast historical data which grows as we work with more clients. We are not a data aggregator and as such we do not sell our database. Instead, we use our database to feed our ML models and help us in the data cleansing and enrichment process.

The technologies we use are not new, but the way we incorporate each one of these in our workflow is what brings out the best of them. This not only allows us to clean and process our clients data, but also do it in record time, thus allowing the customer to reduce losses and make better data-driven decisions.

We also offer the possibility to reach out directly to suppliers or even collect information on premise, thus allowing us to create data that is not yet available elsewhere.

We are proud to say that we are one of the few companies in the business which takes full responsibility for the data we provide and the first to offer a warranty on costs directly associated with the data provided by our solution.

Our solution allows us to perform the following actions:
Enhanced the customers master data structures adjusting it to their digital strategy.
Automatically validate and correct data using previously defined business rules.
Retrieve missing information using our proprietary tools to enrich our customer’s master data with an average of over 90% completeness.
Optionally, contact suppliers and visit customer’s warehouse / locations to update records with information not available in other sources.

This allows us to provide our clients with a fast solution to their dirty data problems while keeping expenses down. Their data is maintained as per their requirements and easily adjusted to changes. Our clients can dedicate themselves to their core business and leave us to take care of everything else. We not only give a one-time solution, but also offer a recurring service for maintaining old and new data that enters their systems, allowing them to decrease the time-to-market of new products launches or availability of data for their BI systems.

Competitors

We identified several halfway solutions that don't sum up to the completion quality and usability that companies are in so much need, such as: image recognition like DataX, Appi vision, web scrapers as Import IO, MDM solutions as Stibo Systems, Akeneo, Informatica, Sales Layer, that only extract data, MKT Agencies that enrich with no escability or technology and Consultancies as well that can guarantee quality but not quantity, Internal Company Teams (Agustina del Valle) that generate high cost, low quality and poor quantity.

All of this 47% expensier than B&L solution understanding the number of services, quality, volume and pricing.
All other solutions can work as a complement for our solution from the sources point of view.

From our Benchmark Companies received a larger number of solutions a higher quality a exponential increase in volume of data for the best competitive pricing available gaining control of data quality, data completeness and data creation.

Advantages or differentiators

Data is the new oil and DataQ is the first automated data refiner. Currently tools such as ERP, MDM, CRM are vehicles to manage and govern data, but none is responsible for the information generated within them. , leaving this task to the different user profiles, with different visions of how this information should be created, which represents a risk for the company that can affect up to 12% of its net sales. With B&L all data that enters its systems or is published in any of its channels is correct, approved, complete and structured to be able to feed all systems and sales channels.
We are the sum of different technologies and the improvement of processes: The only ones in Latin America to use technologies such as document understanding and web scraping in the same collection process; allowing us a higher level of productivity than the competition.
We make scalable the creation of data and information that grows in the world at 40% annually, in the generation of new and updated data, ensuring its quality, structure and completeness. (A job that today is largely done manually, as a repetitive task that does not generate value given its high level of errors)
We deliver a customized service according to the needs of our clients, making the structures that feed all their systems and channels more flexible (we do not impose our way of working).
First to develop for the Spanish-speaking market.
Strength, conviction, drive, flexibility and ability to do this job anywhere in the world.

Finance

Our business model includes a SETUP cost that is paid upfront for the onboarding and activation of a new client, then they buy different options of data consumption per month paying a minimum number of data registry and there forward, in a 12-month subscription model with automatic renewal.
the SETUP starts from USD$639.66 up to USD$6,396.61 depending on the number of Data registry that they are looking to have in the first year and then the price goes for the number of data registry that they need to consume buy month, having one minimum that they pay if they use it or not and for everything above they pay the extra registry, with an unit value starting from USD $5.39 for registry down to USD $3.31 per Registry depending on volume. This leaves us with a 70% net margin.

Business model

Although Data Governance adoption has been positive in the last couple years, its growth rate is still very low, making it more difficult for companies to understand the importance of our solution. Nevertheless, this also means that there aren't many solutions in the market at the moment which gives us a unique opportunity to position ourselves as leaders in Latam. As of today, it takes on average between 6 to 8 months to sign a contract with large companies and between 3 to 5 months for medium-sized companies which increases the risk of contract failure. We currently address this issue by maintaining our sales pipeline in continuous growth thanks to the help of our sales team and strategic partners. Finally, there is the risk of other software companies (which we consider as partners) for them to open the same line of business, but we see this as low risk as it deviates from their core-business.

Money will be spent on

The grant will go mainly in helping us bundle our existing automated services into a SaaS, allowing us to provide an integral solution to our clients, adding one senior full stack developer and one junior developer to the dev team.

Train, retain and attract better talent with special but non exclusive focus on Development, MKT, Pre- Sales, Sales, Post- Sales and Customer Success Manager and business development.

Taking in one new Sales Executive to focus in Peru, and one new pre sales located in Mexico.

Finally, a portion of the grant will be used for visiting new leads and clients in Mexico, Brasil, Colombia, Peru and Argentina.

Offer for investor

This will be discussed in the meeting and process negotiation

Risks

Our risks are:

HORIZONTAL INTEGRATION MDM, ERP (The Mitigation will be Responsible for the data >Potential Partners/M&A)
CLOSURE LEAD TIME 6 to 8 MONTHS (The Mitigation will be Sales team in constant training and KPI focused on generating 5 qualified leads per seller per week, 3 weekly opportunities of closure between 14.000 USD y 20.000 USD, Specialized area in the prospect generation and After sales area and CSM)
INTERNATIONAL TURNOVER THAT INCREASES VALUE FOR CLIENTS UP TO 30% (The Mitigation will be If there are 2 or 3 clientes a subsidiary can be formed to decrease the costs)
INTELLECTUAL PROPERTY (The Mitigation will be Brand protection in 9 and 42 classes )

Incubation/Acceleration programs accomplishment

Participation in Growth Start Up (Start Up Chile)
Participation in The Growth Accelerator
Participation in SkillGravity
Participation in the Unicorn Battle

Won the competition and other awards

We were the third winner in the Unicorn Battle of 2020 that took place in Brasil during November

Invention/Patent

B&L consults with Pablo Saenz de Santa Maria, an expert lawyer in intellectual property matters.
Patenting softwares can bring more disadvantages than advantages since protection processes are not contemplated in Chile and in other countries the costs are very high with uncertain results.
We believe the protection is through the brand, beginning its registration at Inapi in Chile and then in Peru and Mexico for, DataSolution and B&L.
With the proper resources, the first thing is to verify the feasibility of the mark, which consists of the revision of the marks already registered or previously requested, in which it is verified that there are no same or similar marks that prevent the registration of the mark that is sought to protect, with This seeks to avoid future oppositions or substantive observations.
Once the feasibility is verified, the marks are processed in these classes:
-Class 9 related to software [recorded programs]; computer programs [downloadable software]; downloadable applications, computer programs and software, etc.
-Class 42 related to technological services, design, software development, etc.

Photos

Photo 1 - First Data Refinery

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Idea
Current Status
Market
Problem or Opportunity
Solution (product or service)
Competitors
Advantages or differentiators
Finance
Invested in previous rounds, $
Business model
Money will be spent on
Offer for investor
Team or Management
Mentors & Advisors
Lead investor
Risks
Incubation/Acceleration programs accomplishment
Won the competition and other awards
Invention/Patent
Photos
Product Video