Before the age of big data, successful marketing guidelines didn't seem complicated.

Master the 4P theory of marketing - product, price, promotion, channel, when marketing challenges, as long as the use of well-known marketing programs, coupled with good products and beautiful advertising, can basically achieve marketing objectives.

And into the era of big data, all marketing behavior and consumer behavior are data, marketing has gradually become a digital game, data analysis and data management has become the core competitiveness of marketers, data throughout the marketing process.

However, in the face of such a large amount of data, many brands do not know where to go.

On the online platform, China is one of the most advanced countries in the world, resulting in an unprecedented amount of consumer behavior data.

The good news is that marketers have a wealth of information to use. The less good news is that it's not always easy to determine how to handle and analyze the data to reveal insights that are valuable to the brand and hidden behind the data.

As we all know, every business has a wealth of data on consumer choice. However, the wealth of information does not mean that we have a good decision to make with higher conversion rates.

Therefore, we need marketing analysts to help us interpret data and use analytics to provide information and justify marketing decisions.

In the advertising circle a famous saying: I know my ads waste half, but I do not know which half is wasted.

At present, more and more enterprises under the guidance of big data thinking advertising, advertising can be targeted by the crowd, to the accurate target customers.

In particular, Internet advertising can now be based on different people to publish the most suitable ads, at the same time who saw the ads, read how many ads, can be in the form of data to understand, monitoring, so that enterprises better evaluate the effectiveness of advertising, and thus also make the enterprise's advertising strategy more effective.

No target consumer's precise positioning, blind promotion, is a lot of enterprises to carry out marketing promotion has no effect or little effect of the main reason.

An important feature of the big data era is the ability to collect and analyze consumer-related information data in real time and comprehensively, so that they can be targeted and accurately marketed to the products or services that best suit them based on their different preferences, interests, and buying habits.

On the other hand, through timely and dynamic update, enrich consumer data information, and use data mining and other technologies to predict consumers' next or deeper demand early, and then further increase the promotion efforts, and ultimately achieve a great increase in revenue;

Traditional marketing product strategy is mainly, the same packaging of the same quality products sold to all customers, or the same brand, a number of different packaging different quality levels of products sold to a number of relatively large groups of customers, which makes many enterprises more and more products lose the appeal to consumers, more and more can not meet the personalized needs of consumers.

Through the analysis of the relevance of big data, customers and products are connected organically, the user's product preferences, customer's relationship preferences are personalized positioning, and then feedback to the enterprise's brand, product research and development departments, and the introduction of products that match the personality of consumers.

In the data age, enterprises can understand the new, conversion, customer unit price of each channel through data analysis, through the analysis of different channels of users", find those false traffic channels, to avoid false traffic encroaching on the advertising budget, while finding "quality", "quantity" of high-quality channels for large-scale promotion, improve marketing effectiveness.

Data mining and analysis and will be hidden in the vast ocean of data treasures salvaged, channel data fusion to improve the accuracy of precision marketing, visualization technology to complex data polished into intuitive graphics, making it easy to understand, all available tools and means, complete data server cluster, provide strong and stable data computing power, real-time insight into consumer behavior, timely response, mobile terminal popularity, so that data analysis is feasible everywhere ...

Big data marketing enables marketing actions to be targeted, traceable, measurable, and optimized, creating a data-centric marketing closed loop and a virtuous circle of marketing actions.

In addition to the basic concepts and models of marketing analysis, the editor also wants to become a marketing analyst's small partners, can look to the future, the following three trends are worth remembering, in the interview to talk about the following views, so that the interviewer can look at yo! 

Traditionally, many organizations' business decisions have relied on large, centralized managementA data server or data warehousemarketing analysis. But now, we've found that analysts also need to find out what's stored in many "small" data warehouses.

In addition to the usual internal data repository, market analysts need to extract data from dozens of separate systems, including:

Taken together, these data sources will provide better marketing and sales insights than internal systems and will help businesses drive consumer interest, optimize pricing, and improve the customer experience.

So analysts must now do more than just analyze. They must also determine where important data is located, identify what needs to be extracted, and develop strategies to drive business decisions based on new data sources.

The speed and volume of data obtained has now increased to a level that human data analysts cannot fully process. 

To help, many companies have sprung up to provide market analytics and artificial intelligence (AI). These systems use machine learning and other artificial intelligence techniques to help analysts find patterns in customer data, suggest performance optimization, and allow non-professionals to access complex analysis in simple languages.

For example, Hyper Anna is a marketing agent that provides machine intelligence venture capital support to marketers, and Ta summarizes models that can play an important role for the target company after receiving company-related data.

This means that hyper Anna can summarize and refine cross-sell and up-sell opportunities and provide advice on revenue forecasting and supply chain management when the target company uploads relevant marketing data, such as customer interactions, financial performance, and supplier activity.

Another company, Datorama, offers "artificial intelligence-driven marketing intelligence", which makes it easy for marketers to unify data across systems and access powerful analytics in natural languages. David points out that Datorama is now integrated with Amazon's Alexa and provides voice-activated marketing analytics.

While the marketing analyst toolbox has traditionally consisted of skills such as SQL, business analytics and Excel, marketing analysts in 2018 are likely to tell stories more than collecting data and producing reports. 

Use these new data sources and AI tools to market data analystsThe daily work of the future, which becomes: 

Just creating a dashboard and sending weekly reports is not enough. All the information, data, and observations gathered from digital marketing analytics tools make sense only if marketing analysts pay more attention to their customers and figure out what's behind the data.

The true value of analytics is not only to prove the value of marketing to the boss, it can also really improve and improve marketing performance - whether it's a single channel or a multi-channel marketing strategy.

We need to start using data to focus on the future, not just measure the status quo. Track social and search data to form the basis of a "forecasting framework" that provides insight months earlier than market research or sales data. Enables marketers to anticipate changes in brand assets in a timely manner, enabling them to take timely action to address these changes.

In such a changing environment, the ability to have such a "telescope" to look to the future is a very valuable competitive advantage for the brand. This advantage cannot be ignored by any brand.