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6 Lessons in Data Strategy for Startups

Lessons in Data Strategy for Startups

Data can be an intimidating concept for a new company, especially a startup. The paradox is that the agility of a new business and the lack of fixed structures and processes makes it the best candidate for using the insights provided by Big Data to adjust to the market in real-time and provide value. A startup has the luxury of using Big Data results in a way that is similar to giants.

Right now, using Big Data is more accessible than hiring a secretary if you know what to measure and how to use the results. The primary difficulty is selecting the KPIs that fit the company’s strategy.

The most alarming fact is that, as IBM shows, 77% of businesses have not even thought about using Big Data yet. Unfortunately, start-ups cannot rely on business as usual and ignore this trend until it becomes mainstream, or they will most likely never see that day.

Start-ups should capitalize on every competitive advantage they get. Technology combined with outsourcing allows a well-thought small business to become a unicorn, a term introduced in 2013 to designate highly successful companies, valued at over $1 million. Most of these are born digital, just think of Airbnb, Uber, Dropbox. Most leverage the power of Big Data to create smooth processes that feel so natural but are, in fact, the result of carefully crafted algorithms.

Even if not all become unicorns, let’s see some of the areas where any start-up can harness the power of Big Data, regardless of activity sector and revenue.

Define the Business Model and the Value Proposition

Even before a company is created, the founders can use data for feasibility studies to identify customer target groups and to draw up a realistic business plan. These readily available records can act as financial advisors. One can assess the size of the market, the saturation degree, the total number of potential customers and the expected demand for a product. With these pieces of information, a founder can decide if the investment is worth it and what their value proposition should be.

Some simple and free tools for business are Google Trends and, more specifically, Google Shopping Insights. The most important aspect of using real data in planning a business it that it takes out the guess work by replacing it with real numbers.

Drive Customer-Oriented Marketing & Increase Sales

Big Data in business was first used in marketing and e-commerce. In his piece for Forbes, Louis Columbus, Big Data specialist, highlighted the areas where it can make a difference in an organization’s marketing strategy, ordered by importance.

Customer analytics takes first place and are mostly used to offer a tailor-made experience. Start-ups should use every trick in the marketing book to attract and retain clients. Delivering a customized answer to their needs is one of the most efficient ways of remaining in business.

Social media and online channels are dissolving market entry barriers and cutting advertising costs. Any dorm-room start-up can new reach millions of qualified leads by smart targeting. The only necessary information is a complete profile of the ideal client and setting the right filters for Facebook ads. The detail level goes far beyond demographics; you can select behaviors, interests and even a relation to a competitor.

Since most of the time start-ups have limited resources, they engage in a beach-head strategy to secure the most valuable customers and use them as evangelists of the products, to reach masses. By using Big Data, the company is not only able to identify the best clients, but scan their social and professional networks to compute their influence potential. This approach has been called the “tribal” model of reducing churn and has already been successfully applied by T-Mobile.

Data can also tell you what your most profitable client segments or even individual customers are. By adapting algorithms that show interest in a brand, you can also find out which clients are about to switch to a competitor.

 Supply-chain management

As a small company, it appears that there is little space for cutting costs, as usually operations are done on the bare minimum. Year-round flat rates can be tweaked to save some dollars or existing data about clients like credit scores can be used in sophisticated models to predict default risks.

Even small realtors, car rentals or zoos can leverage Big Data to predict revenue, make better offers and increase their margins. Data can also be used for headcount purposes or determining the necessary number of contract-based workers for activity peaks.

By looking at the supply chain, a small company can optimize the components like upstream (choosing suppliers and warehouse locations), delivery management and re-ordering. Big data is providing answers to all these questions by predictive analysis. An area with existing customers will most likely lead to new orders, therefore having a warehouse nearby makes business sense.

Start-ups can analyze data and shorten the delivery time, at least for top clients, increasing their satisfaction degree and ultimately their retention rates. Even small changes as correlating the expeditor’s schedule to alerts for the customer can make a difference.

Leverage big data in HR

Using Big Data in recruitment is a disruptive approach. Startups can take advantage of this because they lack the experience of a dedicated HR department, but can compensate with AI. Even if they have no office and conduct the interview via Skype, start-ups can get the best people by employing digital voice analysis, interpreting the candidate’s facial expressions via face-recognition and emotion analysis programs and replacing multiple-choice questions with computer-generated scenarios, based on previous answers.

Using the business intelligence provided by dedicated recruitment platforms such as LinkedIn can help a new company reach top talent filtered by any criteria necessary, such as previous experience, a preferred school or the number of years in management positions. Although widely known, the predictive power of the platform is currently not used enough in companies. Combined with application-specific data, predictive analytics on a profile can determine if an individual fits the ideal candidate or the perfect manager.

Big Data studies will increase by number and become more detailed, correlating information from unstructured samples, such as cover letters or social media profiles. By sentiment analysis and word and grammar scanning, the software will decide if a candidate is a good fit for the team by taking into consideration both know-how and personal values.

Check competitors

Your data can be used to see how your organization is doing when compared to competitors. The number of followers, website visits, check-ins or even the social buzz are all indicators of how you measure up. If you want to keep a record of what is being discussed online about you versus competitors, activate alert tools such as Google Alerts or SocialMention. If you want to see how your business compares directly to theirs, just do so by using tools like SimilarWeb.

Snoop on the terms your competitors use online to get clients with Semrush and Monitor Backlinks. Data can also show you what the terms your competitors are using in paid advertising and help you assess what the opportunity costs are. Depending on your specific needs, there are new tools created almost daily that make strategies transparent.

Find Investors

Big Data has already been used for high-frequency trading and creating investment portfolios by looking at the company’s financial performance data. However, the roles can be reversed, and small organizations which are looking for financing could ask Big Data consultants to create profiles of the investors or venture capitalists who have previously engaged with similar companies.

The algorithms used in such a case are no different from those used for creating user profiles or creating ideal employees’ profiles. It is all about defining the measures and the weights.

Having the profile of the most likely investor or even a cluster of possible investors supplied by real data, not just hunches and hopes can help a start-up create better pitches and reach out to the right people, shortening the time until growth.

Conclusion: Close the IT gap

As technological barriers are no longer an issue, small companies have access to the same data and technologies as large corporations.

The lesson to be learned here is that it is okay if you were waiting to find out more before joining the Big Data bandwagon, but you should take some steps in that direction as soon as possible.

Now it is a moment of “data democratization,” which start-up can seize even with limited resources. Companies offering these services have already assessed the size and potential of the SME market, and self-service analytics systems are beginning to pop everywhere, helping companies make sense of the data to secure a market share.

A Big Data solution could mean an initial financial effort, but if chosen carefully, such an approach, is one of the best investments, producing ROI in the first year and offering all the benefits previously discussed.

Published: October 12, 2017

Source: Array

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