Taking Market Research to the Next Level

Data sits at the core of every business, big and small; the market itself is data-driven, so it is easy to see how good use of data in decision making can lead to business success. In the era of the internet and social media, data has become even more important as a part of business operations.

While the use of information, insights, and data from various sources is critical, however, not all businesses utilize data to their advantage. Even when the operations are data-driven, businesses may still find themselves at a disadvantage in terms of data use.

Bigger corporations like Amazon have better data gathering and processing capacities. They have the ability to understand the bigger picture in a more holistic way while maintaining a detailed view of individual segments of their operations. Unfortunately, small enterprises don’t always have that capacity.

There is a large data gap between large corporations and small businesses, or SMBs. That gap is being closed by solutions such as cloud computing, AI, and analytics tools. Can your small business benefit from these solutions?

The Enterprise Approach

Before we get to what you can do to make your small business more data-driven, we need to take a closer look at how bigger enterprises gather and process data. Amazon is a good example of data-driven operations. For so long, Amazon has been using data from multiple sources to better understand their customers.

The closest and most accessible data about customers can be found in their interactions with Amazon. The products that customers buy, the way they interact with Amazon’s website and app, and even details such as demographics and spending habits all lead to a better understanding of the target customers. When processed, these details produce relevant, contextual insights.

Contextual is the key here. Amazon has the ability to recommend products in a more personalized and accurate way thanks to relevant and contextual insights. At the same time, they can optimize their use of advertising and marketing campaigns by taking note of where in the customer journey the targets are. More importantly, Amazon can refine its use of data and boost their return on investment, or ROI.

Having mastered internal data collection and processing, Amazon now turns to external data. Social media posts, product shares and discussions, and other insights available on the market are also collected and processed. This is what we now know as big data. Using Amazon’s massive computing power, data can be processed to produce deeper insights.

Closing the Gap

Data scraping or gathering and processing at such a massive level is not always possible for SMBs, but that doesn’t mean there isn’t a way to close the gap. In fact, the solutions available today make it possible for small businesses to take active steps towards understanding their customers – and the market as a whole – better.

Small businesses can turn to a data intelligence company to simplify the process. With data scientists and strategists working around the clock, that small data gathering and processing capacity can be expanded. Even better, working with experts means businesses – including your company – can benefit from the collective understanding and experience of the experts.

The only downside to working with a good data intelligence company is the cost. The cost of using available data intelligence services can be too high for small businesses with a limited budget. It is also difficult to justify the steep costs when the business operates on a smaller market with less margin.

Another alternative worth considering is performing data gathering and processing in-house. As mentioned before, collecting and processing your own data is very easy to do now that there are solutions like cloud computing and AI to help you. Not only will this option be friendlier to small businesses, it also gives businesses more control over the data and insights produced by the process.

Data as a Process

The process of building an internal data gathering and processing workflow begins with understanding the insights you need for better, more data-driven decision making. List the insights you need to boost your business operations and work on details and strategies on how to collect relevant data.

The infrastructure side of the equation is the next challenge to solve, but this is a problem with many solutions to choose from. Cloud services such as Amazon AWS and Microsoft Azure are designed with big data and data processing in mind, and they require no large initial investment; cloud computing is perfect for small businesses indeed.

Next, you need a way to scrape and process data. There are two ways to integrate these processes, the first one being developing a proprietary script for data scraping and processing. It requires technical know-how, but it offers more flexibility in return. You can choose how insights are produced down to where to best find relevant data.

Another option is to buy a script that suits your business’s needs the most. This is the easier and more cost-efficient way of the two, plus it allows you to start gathering data immediately. With more businesses, especially SMBs, investing in data-driven business processes, the number of ready-made scripts available is on the rise.

Before you can start collecting data, there is another challenge to solve: security. Running scripts to collect data from multiple sources is not something you can do out of the box. You need a proxy pool for two important reasons. First, the proxy pool acts as a middleware between your business and data sources; it allows for more neutral data gathering, as your data will not be affected by noise (i.e. browsing history, location, etc.).

The second reason is protection against an IP ban. When the script runs from a single IP, it is easier for data sources to recognize your attempts to collect data, which means it is also easier for them to stop you from gathering more by banning the server’s or your business’s IP address.

These solutions let you approach data as a process. They offer the right ingredients for an efficient data gathering workflow. Processing the data is a matter of pooling data and running the entries through a routine; you can use a sheet program or go a step further with automation.

An Available Solution

Closing the data gap is something you can do today. All of the solutions we have reviewed are readily available. More importantly, they are very accessible thanks to their affordability – the lack of big initial investments to make means data gathering and processing is more accessible than ever.

Modern startups use the same approach to stay true to their data-driven nature. Startups don’t generally have a big team of data scientists. The rely on a lean team of one or two people and turn to solutions like cloud computing and automation for the rest.

The result is a set of insights that allows you to make better decisions. Data lets you do so many things, from delivering better products and services to customers to actually adapting to market changes faster than ever. When you take the extra flexibility, the ability to adapt, your closeness to customers, and the resources you have as a small business into account, data becomes the final ingredient that pushes your ability to compete with big corporations to the next level.