Questions that find their answer in Big Data, a fashionable concept among IT companies and especially in Big Data Marketing. But can only IT companies benefit from it? The truth is: No, there are companies like GroupM, one of the largest advertising agencies in the world, which has centralized its Big Data in a single office in New York, saving $120 million. Macy’s, the American department store company, has reduced the time it takes to optimize price changes from 27 hours to one hour, even though it has 73 million items!
This shows the reach that Big Data has. Companies that use Big Data to understand who their potential customers are and what they need may be able to be more responsive with their products and/or services. But what does this have to do with digital marketing? Everything, Big Data can provide online marketing with the methods and tools it needs to improve results.
The difference between analytics and management applications and what is meant by Big Data is that the latter can be really useful for online marketing, because you need a lot of data to better understand users, generate more engagement and sell more. And Big Data excels at:
That’s because ordinary software can’t handle the huge amounts of data we’re talking about here. In fact, Big Data is defined as a complex amount of data that is difficult to process using only database management systems and traditional processing applications. The amount of information we receive from users is fundamental for all digital marketing actions.
This is because there are different information formats that need to be considered and that Big Data processes (text, graphics, images, videos, multimedia, etc.). Because the information comes from a large number of devices. And because the digital sources of information are diverse. Big Data needs a different technology than the information that is processed in the datawarehose. To make the diversity useful for online marketing, it must be possible to structure this information with tools that facilitate its collection, analysis and interpretation.
Because data arrives and is processed quickly, and decisions can be made in near real-time. For this reason, companies must also be prepared to react and respond with the best strategies. Consumer habits and user preferences can change from one day to the next, and managing this information can help find solutions in the shortest possible time.
Does the recent crisis at Samsung remind you of anything?
Because you have to be able to obtain relevant data that you can trust. If the data is not reliable, it is useless, no matter how many of them we get. For this reason, we need to be able to measure and evaluate the quality of the data we get from Big Data.
Imagine in 2008, the article “Big Data Computing: Creating Revolutionary Breakthroughs in Commerce, Science, and Society” stated that: “Just as search engines have changed the way we access information, other forms of Big Data computing can and will transform business activities […]. Big Data computing is probably the biggest computing innovation of the last decade. Today we have just seen the potential of collecting, organizing and processing data in all aspects of our lives […]”.
What does Big Data contribute to digital marketing?
Translating the characteristics of Big Data to online marketing, we find that it has great practical applications for more precise, focused and productive campaigns:
What are the benefits of Big Data for online marketing?
1. Structuring and monetising data
Have you ever lost information between departments? Unfortunately this is a fact of life in many companies. To generate content for our strategy, we need quality and up-to-date information. Losing information is a luxury that we cannot afford nowadays. Big Data is able to create a unique data structure, so that each department can take advantage of the information it needs at any given time.
2. Segment your contact base
Segmentation is a fundamental practice in any digital strategy. It is important to divide your contact base into groups or segments based on similarities and trends, in order to create more attractive and relevant content for them. Nowadays, with Big Data, you can find out how these contacts are evolving every week: what they buy, how often they buy, how much they spend, how they respond to the brand, etc. In this way, we can identify their consumption patterns and classify them into justified segments.
3. Personalise marketing strategies.
From this segmentation derives personalisation, which is the future of marketing. Knowing your ideal customer or buyer persona, as we say, is essential. Big data offers the great possibility of analysing data that is not only demographic, but has to do with tastes and preferences to personalise the experience that the contact has with the product and / or service of the company.
4. Get more sales opportunities.
Having more information allows you to generate more targeted content for your potential customers. If these consumers are satisfied with the way you satisfy their consumer need, it will be easier to get more sales opportunities, thus avoiding churn.
5. Guide consumers
Are you familiar with the buyer’s journey? This is the buying cycle that every consumer goes through. In digital marketing it is essential to know what the needs of the buyer persona or potential customer are at each stage. With Big Data, key data can be extracted from each contact to guide them through the buying process.
What types of data should you take into account?
The practice of discrimination is a constant in marketing. It may seem negative, but the reality is that if we are clear about our objectives we can think about the kind of information that should be analysed to solve problems and improve strategies. Big Data offers a huge amount of data, which is why it has to be classified.
- Web and Social Media. It is the web content and information obtained from the different social media platforms and blogs.
- Machine-to-Machine (M2M). These are the technologies that allow you to connect to other devices such as sensors or meters that capture data that is transmitted to other applications that translate this data into meaningful information.
- Big Transaction Data. Includes billing records, in telecom call detail records (CDRs), etc.
- Human Generated. Users also generate large amounts of data such as information stored in a call centre, voice memos, emails, digital documents, etc.
As you can see, there are places to start. Use analysis and management tools and think that investing in knowledge will always benefit your company.