Embracing a new business analytics strategy
How a good data analytics strategy can generate new business opportunities
In order for one company to have a successful business strategy, it needs six essential things: smart planning and goal setting, constantly improving product, appropriate marketing channels, efficient and optimized operations (thus, low costs), and competitive advantage. Of course, those are affected by endless other external and internal factors, which organization do not have direct control of, such as changing trends, customer behavior, economics, technology, political and legal grounds.
However, in today's highly competitive world, it is not enough to have a great business growth strategy. One other essential key “booster” for business opportunities, successful development, and profit growth is the implementation of a good data-analytics strategy, which to be in alignment with, and support the established goals, objectives, mission and vision of the organization.
Why Data analysis strategy is important
Until a few years ago, data analytics was something that only big corporations adopted, and they were still not sure how to use the gained insights to attract new possibilities and enhance their business development. They simply analyzed big datasets, without prioritizing, planning, or goal-setting or aligning them with the already established objectives. However, analyzing data without any objective in mind can be considered as a loss of resources and can result in missed or unused benefits, advantages, and opportunities.
On the other hand, aligning data analysis with business strategy generates real value, gives answers to complex questions, and provides a solution to key organizational issues.
In 2019, data analytics has become an essential part of every entity's development. According to the International Institute for Analytics, businesses using data will see $430 billion in productivity benefits over their competition not using data by 2020. Entrepreneurs, managers, and small-business owners have realized that “data” is not a term that only web developers and ITs refer to. Moreover, they have recognized the potential of Big data, Dark data, and Real-time data in growing their business.
No matter the company size or business model, the collection, analysis, and interpretation ensures identification of new business opportunities, triggered by better understanding of the customers' behavior, market, trends, competitors, weaknesses, and strengths. And the stronger the data analytics strategy, the higher the potential of organizational possibilities.
But how exactly great data analytics strategy generates new opportunities? The key is not to base business goals entirely on data insights, but to use those insights to see how you can achieve your already set goals in a smarter, more efficient way. Let's see some examples.
Expanding the customer base by targeting a new customer segment
Imagine that company X wants to expand its client base. So its objective, or goal, is “To sell products and services to new customer segments.'' Instead of launching generic surveys, asking if people would become customers, or targeting all kinds of people who are not clients of the organization, proper data analysis strategy provides a smarter solution.
For example, by evaluating the data that the company is already creating on their customers, and generating goal-driven insights, the organization can identify patterns in the users' behavior, and recognize what kind of people are already clients of the company, without being targeted. This way, data analysis helps the company to identify a new business opportunity for targeting new consumer base.
By conducting some more research, the organization could see the motives and desires of the new target group and approach them accordingly, to convert them into paying customers.
Using new marketing channels to attract new customers
Currently, many international business entities start creating blog and vlog content to enhance their marketing strategy with the purpose to reach new customers, establish authoritative market position, increase their sales volume and grow their profit margin. Yet in 2016, 61% of businesses have used video as a marketing tool, and until 2019 this trend has been growing tremendously. As a consequence, many companies decide to follow this market trend in order to keep up with the tendency.
Nonetheless, blogging and vlogging for business is not an ultimate solution that suddenly rises companies from the ashes.
In this case, however, a high-quality data analysis strategy can help the organizations to identify their niche business opportunity, and leverage skills for blogging and vlogging.
If the same company X establishes the objective to “Attract customers through new kinds of channels”, it would have to adapt the data analysis strategy to this particular goal. Then, by collecting and using appropriate data to generate insights, the organization will be able to see what kinds of channels its customers are using the most, (it would be ideal to recognize channels that the company does not target, or does not have a presence in) and apply the information as a benchmark to identify what other customer groups are using those channels. For example, company X does not have a Youtube account, yet 85% of its clients use youtube on a daily basis.
The next step is to distinguish which people that use Youtube would be interested in watching videos, related to the industry, which the company operates in, and what percentage of those people are actually potential clients (which would increase the conversion rate).
By following those steps, company X would be able to identify if the market trend for blogging and vlogging can bring any benefits and advantages to its growth and development. By using tailored, goal-driven data analysis, the organization will clearly and unbiasedly see what business opportunities exist and will evaluate if they are worth financial and asset investment.
Tips on how to establish high-quality data analytics strategy
Clearly and in detail state your business objectives. What do you want to achieve? What is your goal? Try to be as specific as possible and DO NOT generalize your goal as “I want to be more profitable”. Use the SMART (Specific, Measurable, Achievable, Realistic, and Timely) criteria to create your objective.
Identify which type of data will best suit your business objectives: Big Data, Small Data, Real-time Data, Dark Data, Smart Data? Choose the right type in order to get the best out of your analytics strategy.
Decide how the data will be collected. Is it going to be externally or internally collected? What kind of method would be used? Do you have the right technology? Those are all questions that will help with the creation of a proper data analysis strategy.
Determine how to turn the data into insights. Are you going to hire new, skilled people or train somebody from the existing employees? Will you contract a specialist or establish a partnership with another company to outsource this activity?
Educate yourself about the political and legal aspects of data collection and analysis: GDPR, data ownership, security, privacy, risks, and liabilities. Being aware of those details is crucial for the smooth implementation of the data analysis strategy.
We can gain opportunities for business growth and take advantage of them only when we ensure that we have prepared high-quality data analytics strategy. Yet, such a strategy is key for effective planning, goal-setting, risk-evaluating and decision-making processes, which are the foundation of every team, department and business entity.