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Two Ways Data Science Can Help Your Start-Up


Even before the rise of big data, small businesses and start-ups relied on data analysis to predict the best location for their business and the best means to deliver products to their market base. Too frequently, the market analysis was the extent of non-tech businesses' adoption of data science. However, non-tech-driven companies benefit from data science technology. It simplifies data collection and fosters dynamic, real-time insights throughout a business's lifecycle. The following two data science trends can help even the smallest business remain competitive.


Personalization at Scale


Legacy data has been beneficial for traditional businesses. Long-standing companies can use data science technology to parse through customer spending habits, seasonal changes, product preferences, and other factors as a means to gain better insights into the products consumers will likely want in the future.

Start-ups do not have legacy data, but that might be a good thing. Zach Bennett, the CEO of Bennett Data Science, told Entrepreneur that segmenting customers into categories based on gender, age, and previous buying history is one way to gain insights, but "[t]hat's not personalization, it's segmentation."

Start-ups can bypass old marketing techniques like segmentation and embrace new techniques like personalization by viewing customer behavior through customer actions. For instance, start-ups can gain insights directly from the customer by employing onboarding questions, surveys, and other interactive media. This moves the start-up away from segmentation and into personalization.


Efficiency and Growth


The job title "Data Scientist" is becoming an outdated term. Today's start-ups hire marketing team members, sales team members, product designers, and others who have experience or education in statistics, data engineering, or other data-disciplines. The reason for this has to do with the need to integrate aspects of data science throughout a company. Data-driven companies cannot depend on a separate data department. Each unit must develop data-driven practices and mindsets to create the kind of efficiency that spurs increased profit and future growth.


Start-ups are in a position to build data practices into their workflow from day one. In doing so, data professionals won't work in isolation. They will be part of a highly successful organization or team that makes decisions based on the best available insights in real-time.