Despite global fundraising activities being hit by COVID-19, APAC-focused Private Equity and Venture Capital (PEVC) funds are outperforming those in North America and Europe. APAC-focused PE funds also recorded another year of robust growth in 2019, where a lot of dry powder is piling up in private [...]
Learn why startups should collect data, what data they should collect, and how to set the right ethical standards for using that data
During the early days of a startup, a hundred different things demand your attention as a founder, and data collection may not top your list of priorities. However, data collection is crucial not only for large corporations, but even for startups.
Tracking data-based metrics can not only help you forecast your revenues to attract investment, but it can offer key insights about your target customers, how they are interacting with your brand, and their opinion about your product or service.
“I have a fundamental belief that data is the lifeblood of business. Without data, you can’t plan properly, you don’t understand your customers properly, you don’t know what your sales are like. So, it’s incredibly difficult to run a business without data, particularly in this day and age, as your customers may be not just from your local area, but could be from anywhere around the world,” says Robinson.
Benefits of data collection
Data is an essential tool that helps with effective decision-making. It can point out flaws in your product and your company strategy. Even if you have years of experience in a field, data can indicate whether you’re headed in the right direction or not.
According to Robinson, data can cover many things—it can be your sales data, facts about your employees, metrics on your customers, and information about your marketing results. You need these types of data respond with agility to changes in the market climate, to understand if a certain product is selling better, or a certain product is not selling well, or where it is not selling well, and why.
To use a current example, many startups pivoted to services and products they deemed to be essential, or those that experienced a sudden upswing in demand during the pandemic. Such business decisions cannot be taken overnight, or on the basis of intuition, but need a foundation of data to support any sales theories.
Besides, following your intuition may not always lead you to the right path, and having data to support your decisions and rationale can help boost your investors’ confidence.
To take another example, let’s say you have decided to launch your startup in a given target market, and approach investors for funding. In order for them to support your ideas and believe in your goals, you will need data to back your claims. If you think that your product is best suited for consumers in Asia, you need to prove how you arrived at that conclusion, and provide data that supports your hypothesis.
The same is true for expansion plans. If you want to expand your services to another country, or continent, you need to show data that proves there is a demand in your selected market for the services you will provide.
Most importantly, as a founder, you need to delineate a clear path to profitability, not only for your investors, but also to determine the sustainability of your business in the long term. Unless you have data related to all aspects of sales, expenses, and marketing, you cannot calculate your revenues or future profitability.
To calculate and track key metrics that investors are interested in, like Customer Acquisition Cost (CAC), Return On Investment (ROI) of your marketing campaigns, etc. you need to carefully collect and track all data pertaining to these metrics from the very beginning.
These metrics in turn can help you price your products correctly. Data can indicate whether you are priced too high for your target market, or too low to achieve profitability.
Another key benefit of data collection is competitive advantage. Startups need to know their competitors, just as much as their consumers. Data on competition can help businesses position themselves better, understand where they are lagging, and how they can surge ahead.
Perhaps, the most important benefit of data collection is that it helps businesses understand their customers: what they want, where they are from, how much they are willing to pay, what they like or dislike about your products or services, and most importantly, why they are leaving.
All this information can help a startup in the long run, by clearly demarcating areas that need improvement, and where you should be spending more money to earn the most customers and maximize ROI and profitability.
As a database marketing executive said in a Deloitte survey entitled ‘The Analytics Advantage,’ “We’re really not spending money on data analytics. We’re using it to find better alternatives for making money.”
What data should startups be collecting?
To begin with, startups should collect some basic data including sales figures to understand where sales are coming from, how much you’re making, average order values, profitability, and data related to your customers, according to Robinson.
“You don’t have to be a data-driven business to really want to understand your customers and your prospects,” he added.
However, it is easy to be overwhelmed by the sea of facts and figures in this age of information. Therefore, it is essential to segregate your data according to its relevance, and Robinson adds that asking the right questions is a good lead-in to collecting the right data.
“We’re living in a data-driven age where we could actually be swamped by this tsunami of data. So the key thing is to prioritize the data that you’re collecting by asking the right questions. […] And then make sure that you’ve got the data to help you answer that question,” says Robinson.
“You could be collecting all sorts of information about your customers that isn’t that relevant. But if your key question is, how do I grow sales in this region with this product, then you need the data to help you answer that,” he says.
When should startups start collecting data?
“I think from the day they start their business, they should be looking at lots of different types of data,” says Robinson.
According to him, not only should founders look at first party data (data collected directly), but also second or third party data, or data that has been collected by other individuals or organizations. Examples of this include market reports, industry analyses, sales trends in the industry or sector, etc.
“It’s very difficult now to build a business without some data insight behind it, to make sure that you’re moving in the right direction, that you’re selling the right products, that you’re approaching the right market segments,” he adds.
What are the different sources through which startups can collect data easily?
According to Robinson, there are many different types of data sources – but there is generally a clear starting point.
“First and foremost, I’d look at the way that your customers are interacting with you and collect data on that. And that might well be through a call center or through online sources,” says Robinson.
He advises collecting data on who’s visiting your website, how much time they are spending on which pages, and how the traffic flows through the website – data that can easily be collected and tracked through web analytics.
Additionally, you need to determine who is interacting with your brand and content on social media channels, and for how long.
“I think this type of data is actually relatively easy to collect, and can provide real insight. So you don’t have to be particularly data savvy to be able to collect and then analyze this type of data,” says Robinson.
Moreover, you can easily collect, track, and analyze data generated through your marketing campaigns. With Google AdWords, or Facebook Ads, it is easy to analyze what is working for your business, and what’s not.
Data and Ethics
According to Robinson, a lot of consumers are confused between data security and data privacy. But as a business, it is crucial to have proper data security protocols to avoid leaks.
“In terms of data privacy, in my mind it’s all about this concept of value exchange,” says Robinson.
“So, when you’re collecting data, you need to be open and transparent with the consumers that you’re collecting data from, make sure that they know what data you’re collecting, and how you are going to use that data. I think that is fundamentally important. You really have to get that completely nailed,” he says.
According to him, once consumers know what data is being collected and how it is going to be used, it is up to them to decide whether it is worthwhile for them as a consumer to share that data.
But as businesses, it is fundamental to be open and transparent about all the data that you are collecting, and ensure measure are in place to keep it safe from prying eyes.
At present, most countries do not have clearly defined data regulations and laws, although they are increasingly looking into new legislation to control how businesses can collect and use data. Therefore, it is essential for businesses to set clear ethical standards about data collection and use.
According to Robinson, deep down, all individuals have high ethical standards. However, challenges arise when your ethical standards differ from your colleagues’ or business partners’.
“My feeling is that businesses when they start up, they really need to set out what their ethical stance is. And that needs to be agreed across the whole business,” says Robinson.
An easy way to decide on the ethical standards for your business is to put yourself in your customer’s shoes, suggests Robinson.
Ask yourself, “if somebody was using my data in this way, how would I feel about that and would I be happy if a company that I’m doing business with is using my data in this particular way? I think that’s a really good benchmark to understand whether what you’re doing is ethically correct or not,” says Robinson.
You can also ask your customers about how they feel about how you’re collecting data from them, what data you’re collecting, and how you are using them, to further help you set acceptable ethical standards regarding data collection and usage.
This becomes more crucial if your startup works with AI or machine learning, which use vast datasets to fuel their algorithms.
“I’m a firm believer in AI being very, very important, but there needs to be a human element on top of that AI,” says Robinson. “So we need human-aided AI to make sure that the results coming out of that are ethically sound, and morally sound in fact, and also are providing insights that are robust for a business as well.”
With the concept of trustworthy AIs being increasingly scrutinized by industry critics, Robinson believes there is a need for openness and transparency regarding AI algorithms, so that people can review them and make sure that they’re built and operating with the right ethical stance.
Navigating Data Localization Laws
In countries like China that have strict data localization laws, companies are required to store data inside the geographical boundaries of the country, which could be both expensive and cumbersome.
“One way around that would be for businesses to have presence, and have data partnerships, or some sort of relationship in each of those countries,” says Robinson.
However, it can drive up the cost of doing business for certain companies going into new geographies and countries, which could be a challenge, particularly for small businesses and startups, who do not have the resources either in time, people, or money, to open up offices everywhere, he says.
According to him, it is important for startups expanding into new territories to clearly understand the region’s data laws.
“You do not want to get caught out by this because some of the fines are really quite crippling for businesses. So, I would thoroughly recommend startups either having somebody with expertise within the business, or join relevant industry associations that have experts in the field,” he says.
Since this can be costly, Robinson suggests factoring the cost of understanding the data and regulatory landscape in new markets into your market entry strategy.
As said by Eric Ries, the author of The Lean Startup, too many startups spend too much money on building and perfecting a product that nobody wants or cares about, leading to their ultimate failure. This is because they do not collect enough data about their customer’s behaviors, wants and needs.
Though the ethical and real-world consequences of reckless data collection and usage have come to the forefront in recent years, there is no denying the power that startups are able to wield by leveraging data insights. For a startup, perhaps it’s daunting to consider data analytics early in the life of your business – but there are ways and means to do so without infringing on laws or personal privacy, and ignoring data completely could be a terrible mistake.
Header Image by Franki Chamaki on Unsplash