How to develop an effective Big Data strategy
Nowadays, creating an appropriate Big Data strategy is the basis for the success of many digital marketing campaigns. Above all as far as customer care is concerned, the area where the best satisfaction indexes are obtained. Do you know which behavior allows you to better reach your audience?
Developing a Big Data strategy is the first step to do it. In fact, strategies based on data analysis have higher success rates. For example, according to Adestra, brands that activate exhaustive processes and analyzes to improve the personalization of mails, get double the conversion of those who do not.
And this applies to any marketing strategy. A good analysis of the data presents more solid guarantees regarding the achievement of the objectives. And developing a good Big Data strategy to work on is the starting point.
Data to anticipate the needs of your users
A Big Data strategy that is accompanied by an analysis tool will allow you to reach your goals. Because you will not only be able to detect needs and create more complete strategies, but you will have a global vision.
In other words, you can anticipate the needs, trends, preferences and expectations of your target audience to stay current.
Nevertheless there are those who do not pay attention to this topic. And even less to data analysis and segmentation. Do you know that 83% of brands do not manage database analysis?
Big Data strategy step by step
In recent years, the implementation of a Big Data strategy has become one of the most typical activities. There are many brands that have created powerful systems for their customers.
Among them, recommendation tools or product development and services based on user preferences.
What is certain is that many companies are currently thinking about developing a Big Data strategy. And even if you only known cases of powerful companies like Facebook, Google or Netflix you do not have to think that small businesses do not use this technology.
As data-driven strategies become reality, they become an increasingly important factor in competitive differentiation. So it’s time to start. These are some of the tips for developing your Big Data strategy …
1 # Identify your business problem
In fact, identifying the main problem you want to solve is something that is always done before activating a technology. Maybe you want to solve a specific problem. For example, a small company may need Big Data to better identify inventory levels. And at the same time, a marketing agency will need data to better detect and understand its audience.
So, first, it is important to develop a specific list of questions. Check which ones are prioritized and then fix the rest of the problems.
Once you’ve identified the problems, you can start creating a strategy to sort the ideas.
2 # People before technology
An analysis of Cable Global ICT Intelligence shows that CEOs spend only 6% of their time making daily decisions. But when referring to the most important decisions, when data and analysis come into play, this focus increases to 14.6%.
What conclusion can we draw? Do you think it is positive to put technology before people?
Working teams approaching data-driven business transformation let us see what we do internally in some organizations. In reality, we must not prioritize technology over the work a human being can do.
One of the most common errors is the misuse of the same. That is, Big Data is an extra tool. The important thing is not everything you put at your disposal but the fact that you can use the tool to draw useful conclusions.
If your team puts technology before people, help them understand that it’s a tool to work better.
3 # Define the policies to work on
Policies are a vital tool in developing a Big Data strategy. And in fact, before starting work, the key areas to be treated must be thought of. This translates into the area of power, that is, management, ownership of data and areas of responsibility.
The first two have become the most important factors in any company that uses data from multiple sources. Understanding the policies and rules of each source will allow you to avoid problems.
With laws such as the General Data Protection Regulation, you must now adapt to data access policies. And it is here where we store information, permissions and many other factors involved in the development of a Big Data strategy that does not violate the rules.
The five best practices to avoid not respecting the regulation are …
- You need to know where your data resides
- You must know what you can do with them. It is important to know exactly how you can use the data you have. And it is necessary to be able to distinguish between personal data and more sensitive data.
- Always remind your team of fixed rules
- Create a data collection policy. That is, you need to be clear about what you can collect and from whom.
- Report any infringement
4 # Organize all the information you receive as feedback
A Big Data strategy must be completed by everything related to your business. Getting content that comes from a backfeed can be easy, for example through a questionnaire or survey.
All this will allow you to have a clearer vision on how to identify any improvement or adaptation of Big Data to the needs of your company. That is, it will help you detect what you really need.
5 # Future planning
The business scenario changes rapidly. And this landscape requires cunning from companies that need to find out what needs will emerge. This is why planning the future is a good decision.
Obviously you will not be able to determine what will happen in the long run with precision. But Big Data offers you enough information to anticipate the facts.
Even if changes come at the speed of light, you must try to create a structured plan with long-term goals. For example, where does my business go? Are new areas emerging that have to do with technological advances?
Vital advice for any Big Data strategy
The universe of data, like that of technology, varies continuously. The volume of information that is generated does not stop growing. And in the meantime opportunities to learn more about the environment that surrounds us, grow.
These are 3 factors that will help you improve this process …
1 # Choose the correct data
A greater quantity of data from different sources and quality offers companies a panoramic view of the general situation. And the ability to see what was invisible before the eyes improves operations but also the decisions, strategies and experiences of customers bring better results.
Quality always prevails over quantity. And even if you think that to develop a Big Data strategy with more data can help you, if not all are useful, your path will be slowed down. How to determine which data are ideal for your brand?
Try to keep your creative part active
Companies often already have the data needed to cope with commercial problems. But the dilemma arises when the property does not know how to use information to make decisions.
Those involved in operations, for example, may not understand the value of daily data and customer service. And leaders must have a touch of creativity to shape external sources and new data.
In reality, when you create a Big Data strategy everything affects. This is why it is important to know how to manage the information that is collected.
Social media is another source of content where the information provided by conversations, photos and videos are vital. One way to solicit a creative vision of potential data is to ask yourself: “What decisions could I make if I had all the necessary information?”
Identify the relevant data
Sometimes when choosing the correct data, the structures that have inherited data from IT (Information Technology) can hinder them. Especially when it comes to storing and analyzing data. The IT architectures you currently use can prevent data integration and management. So it is vital to anticipate these problems.
The marketing managers working on these aspects have found that identifying and quickly connecting the most important data and then developing a data cleansing process is essential.
2 # Build a business model that optimizes results
Data is essential. To improve performance and anticipate competition, you need to do a good analysis. And above all to have an effective focus that allows you to build a business model identifying opportunities to be optimized.
Patterns based on hypotheses generate faster results and more practical data. Even if you have to remember that any process to determine a model has its risks. In fact, statisticians sometimes create models that are too complex to be usable.
You have to ask yourself several times “What is the least complex model that would improve my business?”
3 # Turn the capabilities of your team
The main concern of managers is that ownership does not trust or understand data-driven models. And this is one of the main reasons why they do not use them.
These problems often arise because of a misalignment between the corporate culture, the skills and the resources to activate the analyzes successfully.
The tools seem to be created by experts and not by users. And few are able to integrate these processes. In other words, the use of big data requires organizational change. And above all in the areas of action that must lead the process.
Develop relevant business analysis
Many initial big data and analysis implementations do not work because they are not in tune with the company’s daily processes and the rules established for making decisions.
Who creates the models must understand the types of business processes that are managed. Conversations with the owners ensure that the analyzes and tools complete the decision-making processes.
The analyzes are essential
Even simple models, most organizations need to improve their analytical skills. To form a structure with daily operations, the owners must consider this essential aspect, in order to solve problems and identify opportunities.
The efforts will vary according to the company objectives. The goal is to provide managers with the intuitive tools and interfaces that will help them in their work.
Big Data is something that must be present in the minds of marketing managers. Especially if you want them to work according to user needs. It will help to ensure that the results are more precise and the objectives are achieved. It will also give you one of the great values sought by companies today: getting to know customers better.
For this, an effective Big Data marketing strategy must be built through the use of digital marketing platforms that manage not only data volumes but the potential to interpret them. And with the metrics it offers regarding email marketing, SMS marketing, landing pages or retargeting you can focus on digital marketing strategies that allow you to achieve the desired results. Do you want to start now?