Hey guys we are at the stage were we are having discussions with developers for our beta prototype. A friend of mine who is a developer offered to serve as a technical advisor. He referred a former colleague who now has his own firm to develop the software. I put him and his colleague the same NDA and his hesistant about signing the NDA he insists just his colleague should sign it but he wlll have access to our UX designs and code. What should we do.
Oi Yee Choo, chief commercial officer of digital securities platform iSTOX
iSTOX, a digital securities platform that wants to make private equity investment more accessible, has added new investors from Japan to its Series A round, bringing its total to $ 50 million. Two of its new backers are the government-owned Development Bank of Japan and JIC Venture Growth Investments, the venture capital arm of Japan Investment Corporation, a state-backed investment fund.
Other participants included Juroku Bank and Mobile Internet Capital, along with returning investors Singapore Exchange, Tokai Tokyo Financial Holdings and Hanwha Asset Management.
Founded in 2017 and owned by blockchain infrastructure firm ICHX, iSTOX’s goal is to open private capital opportunities, including startups, hedge funds and private debt, that are usually limited to a small group of high-net-worth individuals to more institutional and accredited investors. (It also serves accredited investors outside of Singapore, as long as they meet the country’s standards by holding the equivalent amount in assets and income.) iSTOX’s allows users to make investments as small as SGD $ 100 (about USD $ 75.50) and says it is able to keep fees low by using blockchain technology for smart contracts and to hold digital securities, which makes the issuance process more effective and less costly.
iSTOX’s Series A round was first announced in September 2019, when the company said it had raised an undisclosed amount from Thai investment bank Kiatnakin Phatra Financial Group while participating in the Monetary Authority of Singapore (MAS) FinTech Regulatory Sandbox. The Singaporean government has been especially supportive of blockchain technology, launching initiatives to commercialize its use in fintech, data security, logistics and other sectors.
iSTOX completed the sandbox program in February 2020, and was approved by the MAS for the issuance, custody and trading of digitized securities. The new funding will be used for geographical expansion, including in China, where it already has an agreement in the city of Chongqing, and Europe and and Australia, where it is currently working on issuance deals. iSTOX also plans to add new investment products, including private issuances that investors can subscribe to in “bite-size portions.”
In a press statement, iSTOX chief commercial officer Oi Yee Choo said, “Capital markets are transforming rapidly because of advancements in technology. The regulator MAS and our institutional investors have been far-sighted and progressive, and they support the change wholeheartedly.”
The company is among several Asia-based fintech platforms that want to democratize the process of investing. For retail investors, there are apps like Bibit, Syfe, Stashaway, Kristal.ai and Grab Financial’s investment products.
Since iSTOX works with accredited and institutional investors, however, its most direct competitors include the recently-launched DBS Digital Exchange, which is also based in Singapore. iSTOX’s advantage is that it offers more kinds of assets. Right now, it facilitates the issuance of funds and bonds, but this year, it will start issuing private equity and structured products as well. The company’s securities are also fully digitized, which means they are created on the blockchain, instead of being recorded on the blockchain after they are issued, which means iSTOX is able to offer faster settlement times.
We’re considering sending some unsolicited swag (bookmarks, stickers, etc) with a thank you note to our new paying subscribers. Our subscribers are small businesses, though it would be addressed to whoever did the signing up. Some people seem to like those and some see it as junk.
Do you see any negatives to doing this and do you have any other ideas of what else we can reach out with to build a lasting connection?
Genflow, a London an0d LA-based brand building agency that offers an e-commerce and mobile tech platform to let influencers start companies, has raised $ 11 million in funding.
Leading the round is U.K. investor BGF. The injection of capital will be used by Genflow to further scale its offering and for international expansion.
Founded in 2016 by entrepreneur Shan Hanif to help social media influencers develop their brands and extract revenue from their audiences, Genflow combines aspects of a traditional branding agency — such as strategy, design and planning — and a tech company with its own software stack.
This sees Genflow position itself as a brand-as-a-service (BaaS) platform, which helps influencers develop their own digital and physical products instead of promoting other brands, and enables them to launch their own membership club, gated community, mobile app or direct to consumer brand.
“Genflow offers the complete infrastructure from design, development, manufacturing and logistics through to strategy, marketing and content creation to drive revenue and profit,” explains the company.
Genflow says its client base are established influencers who typically have large followings on Instagram and YouTube.
“Genflow allows an influencer to start their own business instead of the traditional brand deals so if someone with an audience wants truly their own audience and business Genflow does that for them,” says Hanif. “We provide them the complete infrastructure to launch a business: design, manufacturing, development, content, strategy and marketing all in one place. This gives us the unique ability to execute to a very high level that drives revenue”.
Hanif says influencers typically approach Genflow either with an idea or when they need help figuring out what brand they can launch. “We use ‘Genlytics,’ our in-house built software, to see what the best brand they can release by checking their analytics, breakdown of their followers, what brands they have worked with in the past and to see how much they can potentially sell,” he explains.
Next, Genflow onboards the client and begins the brand building process, offering broadly two options: Gated content, membership clubs, community and mobile apps, or developing direct to consumer brand with physical products.
The first is akin to having your own OnlyFans, Patreon or social media platform. The second is a classic D2C e-commerce play and includes designing the products, and working with factories to create samples, manufacture the products and then handle all logistics etc.
“In both cases then we plan the launch of the brand, the marketing strategy and then work with the influencer to launch the brand itself,” adds Hanif.
“What’s interesting is that traditionally in startups you find a problem, get a team, some funding then try to find customers. What we have invented is the ‘audience first approach’ where we already have the audience and now just need the right products and it’s instantly a success. The metrics that I see for our brands are not normal: conversion rates that are 5-30%, 20% repeat purchase buys and around 6:1 return on Facebook ads.
“We are proud that every brand we have launched to date is profitable and growing year on year so we know our approach works.”
We all know that the COVID pandemic has created a massive wave of job losses in the U.S. over the last year. So, with all of this economic hardship, one would reasonably assume that the rate of new businesses is at a standstill, right?
Wrong!
Over the past three months, more new businesses have been launched in the United States than in any other quarter in our history: Between June and September of 2020, nearly 1.4 million startups were founded.
Tune in to this morning’s WJR Business Beat to hear Jeff discuss this incredible wave of new businesses:
“If you’ve ever dreamed of carving your own path and doing it your way, now is actually a great time to do just that. While this crisis has undoubtedly turned everything upside down in so many ways, doing that has forced changes in consumerism and ways of doing business that are flinging doors wide open to new opportunities in almost every aspect of business. So, turn this time of crisis into your time of commitment and be part of the amazing wave of business startups sweeping the country today.”
– Jeff Sloan
Tune in to News/Talk 760 AM WJR weekday mornings at 7:11 a.m. for the WJR Business Beat. Listeners outside of the Detroit area can listen live HERE.
Are you an entrepreneur with a great story to share? If so, contact us at editor@startupnation.com and we’ll feature you on an upcoming segment of the WJR Business Beat!
I’ve got some surprising but welcome news to help us all get rolling on this Monday morning. We all know that the COVID pandemic has created a massive wave of job losses in the U.S. over the last year.
So, with all of this economic hardship as the backdrop, one would reasonably assume that the rate of new business startups in this most dreadful business climate is simply at a standstill, right?
Over the past three months, more new businesses have been launched in the United States than in any other quarter in our history.
Amazing, but true. Between June and September, nearly 1.4 million startups were founded. So, the question is, “why?”
Well, the biggest reason: a meaningful percentage of people who have been laid off are at the end of their ropes with the notion of corporate job security. The reality is, one day you have a job, and in an instant, it can be gone.
So, where do you go from here? Look for another job, or do you start a business of your own? Winning or losing based on how much effort you put in and creating your own sense of security has become a very appealing alternative.
Now, I don’t know about you, Paul, but there is something so gratifying and joyous about the idea of people choosing the pioneering and enterprising path of doing one’s own thing and being one’s own boss. Those ideals have been entrenched in our great American spirits since someone uttered the words, “Go west, young man!”
So, if you’ve ever dreamed of carving your own path and doing it your way, now is actually a great time to do just that. While this crisis has undoubtedly turned everything upside down in so many ways, doing that has forced changes in consumerism and ways of doing business that are flinging doors wide open to new opportunities in almost every aspect of business. So, turn this time of crisis into your time of commitment and be part of the amazing wave of business startups sweeping the country today.
I’m Jeff Sloan, founder and CEO of StartupNation.com, and that’s today’s Business Beat, on the Great Voice of the Great Lakes, WJR.
Tell me if this sounds familiar, as a startup founder, you are constantly juggling many hats: marketing guru, product owner, growth hacker, sales master, accountant, and the list goes on.
To keep things in check, you frequently consult reports from a range of third party sources such as Shopify dashboards or Google Analytics. Periodically, you review cash flow and profit and loss statements consolidating more numbers from suppliers, service providers and internal databases.
However, all these numbers tend to be operational in nature and do not generate returns from your own data by providing valuable insights on how to accelerate growth.
At 173Tech, we are often approached by founding teams experiencing many data pains. We created an easy to follow five step principle to help you quickly master your data and generate analytics ROI.
Common Data Pain Points
Below are the top five data pains experienced by many startup founders.
Messy and inconsistent data
To answer a simple question, you have to dig through many sources and each source reports numbers in a different style. After numerous copy-pasting and manipulating with Excel formulas, you realise that things do not add up.
A typical scenario, Facebook claims its campaigns generated £5,000 sales last month and Google another $ 5,000. However, your total monthly sales was £9,000. You then check internal databases for channel attribution. A completely different story again. 30% of sales came from organic sources.
What can you trust and how do you make decisions on next month’s marketing budget?
Data silos
Numbers from different aspects of your business are scattered around in various sources, gathered in different frequencies, and in some instances, being held hostage by third-party tools.
If you are an eCommerce business, you might receive fulfilment costs from your 3PL on a monthly basis, product sales from Shopify daily, and digital marketing spend weekly from your agency, while cost of goods sold is stored in an Excel spreadsheet and updated as required.
How do you keep track of profit margins on SKU level and decide on which one(s) to scale? How would you evaluate it across demographics?
Error-prone & time-consuming manual processes
To answer the profitability question above, you need to log into each source, query the data for the relevant time period, copy and paste into a spreadsheet, then create a master sheet with a range of manually entered formulas applied to various chunks of data. This process is lengthy and difficult to debug with human mistakes possible at every step of the way.
As you scale, this setup will soon become impossible to maintain. We have seen spreadsheets that take minutes to open and even longer to respond to a single change. Various versions of the original spreadsheet are then created to cater for slightly different scenarios, introducing more errors. Additional errors reduce the reliability of your data and result in more time spent on rechecks.
If you cannot trust your numbers, you cannot build a data-driven culture and make data-informed decisions.
Unable to respond to urgent request
Your app is experiencing a steep drop in user activities since last week. This could be due to a wide range of possible factors: new campaigns bringing in low-quality users, bugs in the latest release, new features users do not understand, or server error preventing push notifications. It could be specific to a country or platform or other dimensions. It requires data interrogations from multiple angles.
Your team starts frantically pulling data from various places to pinpoint the issue, while precious time is being lost and your customers continue to churn.
Disconnection between data and business
Often when checking a dashboard from one of your service providers, you are left with the feeling that it was not very helpful. They contain a number of nice-looking charts and total figures but fail to tell you anything you did not already know.
This is expected due to a number of reasons:
These charts typically visualise simple aggregations (e.g. sum, average or count) over generic metrics (e.g. sales or number of customers), without deep reflections on the true health of your growth.
Data is not processed and summarised into meaningful insights based on your unique business model. It is designed as a one-size-fits-all solution and easy to switch on for everyone.
The main issue with generic and out-of-the-box solutions is that sooner rather than later you will grow beyond the box.
The SCALE Principle
By applying modern analytics, we successfully help companies grow efficiently at all stages, from MVP all the way to over $ 100 million run rate and unicorn status.
We formulated our best practice data strategies into the five components of the SCALE principle. It ensures maximum insight generation from your data while removing all your data pains.
Standardise
The first step towards a world-class analytics stack is to standardise business metrics and apply best practices over your entire analytics processes.
Data Dictionary
To standardise business metrics, start with a list of KPIs core to your success and their definitions. Take monthly revenue for example, it is an important metric with many caveats. Does it include taxes, refunds, or deferred revenue?
Create a data dictionary for all your KPIs. Ensure that everyone in your company is well-versed in its contents, and that it is constantly updated as your business and analytics stack evolves. A consistent data vocabulary allows for clearer communications and goal setting between different teams.
Add technical definitions to each item in your data dictionary. This bridges the gap between business and data. It also provides the technical translation for the automation step later.
Analytics Processes
First, select the right tool stack tailored to your usage needs and existing tech ecosystem. Your tool stack should cover automated data delivery, data warehousing, data modelling, reporting visualisation, and version control. Next, formalise your implementation processes covering requirements gathering, prioritisation, development, peer review, and production release.
Centralise
This is where all your data sources come together. Data from all customer touchpoints (marketing, sales, customer support, CRM, fulfilment, costs etc.) is gathered in one centralised location whilst retaining all the information you care about..
The key here is to select the right tools for your data infrastructure for optimum performance and scalability. For your data warehouse, some options include Snowflake, Redshift or BigQuery, depending on your existing tech ecosystem and intended usage. If you have large volumes of data, you might also want to have a data lake to store raw data, using tools like Hadoop or Amazon S3 buckets.
Another important aspect of centralisation is your code base and reporting. Ideally, all your analytics scripts (e.g. SQL, Python tasks) should be easily accessible from one location. We also recommend a single visualisation platform for all your reporting dashboards to avoid disjointed insights.
Automate
Once you have defined the data sources to collate and their destination, you should consider automating the following aspects of your pipeline:
Data extraction
Data modelling
Data Visualisation
Data extraction ensures that information is delivered consistently from all sources at your desired time interval. Some tool options include Stitch or Fivetran. Consider it your logistic guy who picks up the data package every morning and deposits it into your data warehouse.
For all the data packages arriving in your data warehouse, perform data modelling for two key purposes:
Ensure all sources are linked via unique identifiers to create your own single customer view.
Apply the business logic defined in your data dictionary and transform raw data into meaningful KPIs.
We are the creators and maintainers of the open-source data processing and modelling framework SAYN. It covers many task types including Python and SQL transformations and helps analytics teams improve data engineering efficiency by easily orchestrating and automating data processes.
Once created, you can utilise the data models to create dashboards that clearly visualise your KPIs. Best practice is to have a top-level dashboard that summarises key trends and quickly unveils opportunities or issues in your business. Then design a dashboard per business vertical (e.g. marketing performance dashboard, finance P&L dashboard etc). Metabase, a free tool, is a good option as you start your data journey. As your team and data capabilities scale, consider moving to a more robust solution such as Looker.
Learn
Now with your own centralised data gold mine, you can start learning from it.
With an efficient data pipeline, you can train data science models to segment, predict and influence customer behaviours. Customer lifetime value (CLTV) predictions, churn propensity scores, recommender systems, automated consumer sentiment with natural language processing (NLP), your power here is unlimited.
These models can be integrated into other parts of your products and services to create unique competitive advantages. It creates a constant and dynamic learning loop from observing user patterns, creating algorithms, feeding it into your product development and observing new feature usage.
Another element of the learning loop is user testing. To encourage a desired behaviour on your app, your team came up with a number of ideas to achieve it. How do you know which one will be the most effective? Run an experiment and test these options against a control group. Test results should be modelled, automated, and visualised in a dedicated testing dashboard. This will allow you to capitalise on the winning variant early and stop any poor performing test promptly.
Make sure you have a process where all learnings feed into your internal knowledge base and are shared across all teams.
Empower
In our experience, we have seen many companies succeed through leveraging their data and integrating continuous learning and testing into their agile product development. An efficient and democratised data stack empowers all teams and individuals. It is a game-changer for companies embracing it.
For your data science and analytics team, data efficiency and reliability ensure little time is wasted on digging and cleansing data. Instead, they can focus on mining deep product and behavioural insights, and building state-of-the-art algorithms.
For product and marketing teams, a well-structured data warehouse and user-friendly visualisation tool enable everyone to create ad-hoc reporting tailored to their changing needs. It provides timely feedback on current projects and efforts, so one can pivot and adapt quickly as new data insights stream in.
So make sure to train all teams on your chosen visualisation tool. One efficient way is to appoint a data champion per team, who will act as the data power user.
Either you are looking to set up analytics from scratch or upgrade existing infrastructures, I hope this article provides a structured and easy to follow plan to build your own world-class data stack.
If you have any questions or feedback, reach us at hello@173tech.com. We are always happy to chat!
My SEO Tool was having very little traction until I started doing cold calls for 8 hours a day for weeks on end. While it was a bit rocky in the beginning, we eventually reached 7k MRR, and we hope to triple that this year!
Cold calling comes with a lot of rejection and pain, but in the early stages of your business, it's actually just as effective if not more effective than digital marketing.
Here's what I learned:
In the early stages of your startup, you need to be doing thorough market research and having extended conversations with people in your target market.
Understanding their pain points is key.
While this can be done with landing pages and advertising campaigns, it's much more straightforward to just talk with your prospective users.
You can be doing this before you even have a product ready, and this will actually save you hundreds of hours of time.
This idea of cold calling without a product actually works to your benefit because cold calling becomes more difficult when you are selling a product. This seems counterintuitive, as cold calling is directly associated with sales, but this is because the listener will naturally raise their defenses and try to get off the phone when they sense they are being sold something. Business owners are tired of cold callers trying to sell them useless junk on a weekly basis.
Instead, position yourself as someone who wants to interview them or survey them about a certain problem they have.
For example, if you are a student or someone who is trying to break into the industry, a sizable percentage of business owners will happily volunteer their time to speak with you. If you are asking about how you can provide value and what the user is struggling with, it's a much more organic and valuable conversation than trying to pitch your product to someone who is half-listening and waiting for your spiel to end. You can read more about these strategies in this great video by Y-Combinator.
Here's a step by step of what I did:
I started by cold calling every single prospective business in my area. You can find their numbers on Google and read a bit about their sites/services before each call. In my case, the businesses were all marketing and SEO agencies.
Whenever anyone picked up, I would say that we were a student-led startup conducting interviews and that I would love to learn more about their business.
They usually gave me an interview on the spot or gave me an email to schedule a better time.
If they did not give me an interview on the spot, I sent them an email immediately after the call while it was still fresh in their mind. A lot of times they would ignore my email. Either way, I would call back 3 business days later and ask if they got my email. This almost always led to an interview on the spot or an interview that week. When it comes to having people give you their time of day, persistence is key.
After every interview, I asked them if they would like to be updated with my progress as I try to create something that would solve the problem they were facing. If they were interested, I noted that down and shot them weekly update emails. I would also ask for warm introductions to other SEO agencies in the area if I felt the interview went really well.
One thing I was very cognizant about was to never become "sales-y". This is because, at this point in time, the true value wasn't the money that they would pay for our services, but the feedback about their pain points, which could be used to build a great product.
As I updated these prospects over email, I would continually ask for feedback and pick their brain until we built an MVP (Minimum Viable Product) that addressed all of their core problems. From there, it was a natural step for them to become paying customers for our services.
Cold calling was anxiety-inducing when I started, but after the first week, I actually started to enjoy speaking and learning with new people in my field. Rejection will always sting a little, but the feedback and exposure were well worth some abrupt hang-ups and cold replies!
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