Shulou(Shulou.com)06/03 Report--

Customer Data Platform (CDP) is an enterprise data application platform that focuses on customer segmentation and crowd insight.

That sounds Internet, huh? What does it have to do with bricks-and-mortar and retail marketing?

Let's start with a few stories.

"He won all his opponents, but lost to the Times."

In 2010, RT-Mart finally replaced Carrefour as he wished after 14 years in charge of Huang Mingduan, ranking first in China's department store retail. However, it was hard for the Taiwanese entrepreneur, who was praised as the "king of six wars" by the industry at that time, to expect that Alibaba, which rose rapidly, completed the equity acquisition of RT-Mart parent company Gaoxin Retail in less than half of the time.

Behind Huang Mingduan's helplessness, the former RT-Mart leader left sadly.

In the consumer goods industry with higher threshold, the game between veteran and new star is also in fierce progress. In the first five months of 2019, Xiaomi TV's online share has expanded significantly to 27.79%, approaching the sum of the three domestic leaders. For the defenders who used to position the millet offensive in the "cost performance", what worries them even more is that in 2019, when TV prices continue to dive, the average price of Xiaomi's brand is extremely strong, and today's Xiaomi TV has entered the domestic first-line echelon of online market brand premium. In some emerging categories, such as the water purifier market with higher gross profit, the average online price of Xiaomi even exceeds that of several domestic first-line brands, which may mean that consumers in emerging markets and traditional brands have gradually drifted away from each other before the same economic cost.

4C and population segmentation

Since Professor McCarthy put forward the basic structure in the middle of last century, the 4P theory has influenced and guided the marketing work of most successful enterprises. After entering the new century, with the rise and popularization of Internet e-commerce, the 4C theory centered on consumer, cost, communication and convenience is receiving more and more recognition and application. Among the four elements mentioned above, cost control has long been valued by the business community because of its timeliness and quantifiability of output; and in channel distribution and retail, communication and convenience are long-term business practices. Relatively, customers who are placed at the top of the 4C are often only one-sided cognition and understanding.

In the traditional market segmentation practice, brands and distributors often divide the market reversely with different product specifications and prices, and design effective segmentation strategies according to them for a long time. However, after entering the second decade of this century, with the capacity overflow of supply chain and the rapid development of online channels, the entry threshold of start-ups has been greatly reduced, and correspondingly, the business model and long-tail products that grasp the characteristics and demands of segmented groups continue to erode the market share of traditional enterprises. Behind the phenomenon, there is a further evolution of the traditional market segmentation theory, that is, to whom to sell first and how to sell it. Only by clearly positioning the target customer group and fully understanding its consumption attitude and value preference, can we sell the right products in accurate channels and with touching marketing. As the representative of phenomenon-level marketing, Jiang Xiaobai, a liquor brand that has completed a sales leap of 2 billion yuan in the Red Sea market in recent years, or Xiaomi mobile phone, which conquered young consumers with "born for fever," is the actual advocate and firm executor of this change.

In fact, long before the rise of online e-commerce, quite a few traditional brands and distributors realized the importance of crowd positioning for product and marketing planning, and invested a lot of energy and cost in market research work. However, an unavoidable problem when using traditional research methods is that they are restricted by their sampling statistics. Decision makers often can only rely on their own experience and business intuition to judge the universality of research results. Long-term and inefficient traditional research is really difficult to support the subdivision and insight of large customer groups.

big data marketing

The arrival of the big data era makes marketing pioneers seem to see a turnaround.

Theoretically speaking, with the support of panoramic insight based on massive user data, the marketing department of offline retail is enough to design marketing and operation strategies for each potential customer that conform to their consumption attitude and value preference, thus greatly improving the sales conversion rate. However, in practical applications, traditional enterprises often have such difficulties, which can be mainly summarized into the following two aspects:

User data dispersion: Big data insight often requires high-latitude data correlation and cluster analysis of customer groups, but in quite a number of enterprises, a large amount of customer data generated every day is often dispersed in multiple sets of internal systems such as sales, logistics and after-sales, forming data islands among each other, and regardless of panoramic insight, it cannot even support the general real-time data access requirements of product and marketing departments.

Business value ambiguity: After breaking the data island, the second problem many enterprises face is that due to the lack of guidance from data marketing methodology, IT and data departments are working behind closed doors, and they are unable to help business departments improve market performance.

In order to solve the above problems, CDP, a big data system with strong business pertinence, came into being.

CDP -Customer Data Platform

Different from pure data system, CDP (Customer Data Platform) is a direct business-oriented application platform. After the data preparation of IT department is completed, the business personnel of marketing and product department can analyze customer group and export results without professional data knowledge, which greatly reduces the application threshold of enterprise inherent data, so that front-line business personnel can get more and faster data support in marketing planning.

Secondly, for a single customer, CDP completes the closed-loop from data storage, data analysis to customer group screening, with which the marketing department can truly achieve "who to take, who to use", greatly improving the pertinence of marketing and marketing conversion success rate.

Taking Singularity Cloud CDP as an example, its core business process can be divided into four links: data integration, customer selection, crowd insight and strategy evaluation.

data integration

Modern enterprises, especially medium and large enterprises, often have customer data from multiple sources. According to its source channels, relevant data can generally be classified into three categories: the first category comes from the enterprise's own channels, such as sales, logistics, after-sales, etc., and such data is generally standardized; the second category comes from cooperation channels, such as launch platforms, etc.; and the third category comes purely from the outside of the enterprise, such as online capture. In the data integration phase, Singularity Cloud CDP first provides flexible and open access and cleaning methods, helping enterprise IT personnel to open user data isolated in various systems to CDP in the form of libraries and tables, and supporting users to visualize ETL for specific business domains. Further, with the help of the ID-MAPPING algorithm unique to Singularity Cloud CDP, future enterprise developers can also identify and match customer data from different sources and lack primary key association, and define a unified customer identification code (One-ID). Through the above method, customer attribute tags from different channels and systems can become enterprise customer data assets with One-ID as the core.

Customer Circle Selection

As the core link of CDP, the customer circle module provides a simple and easy-to-use crowd and attribute label management interface to help users quickly circle the required customer groups according to business needs. For example, using the attribute tags collected by the sales department, business personnel can quickly compare the consumption preferences and consumption intentions of customers in different regions, channels, genders and age groups; as incremental data is continuously generated, this comparison can also be upgraded at the time level to reveal changes in customer demand trends. After the business personnel select the target customer group according to the business logic, the corresponding customer information list can be quickly derived for the next marketing planning and promotion.

crowd insight

For users with higher needs, Singularity Cloud CDP can also provide crowd insight analysis function with preset business model as the core, helping enterprise users segment customers more accurately, thus customizing marketing strategy. Compared with traditional statistical analysis, these big data AI-driven data insight methods often have stronger scenario specificity and business guidance. For example, the crowd consumption attitude and value preference model that automatically analyzes category and brand preference and assists merchants to make joint recommendation, or the RFM model that divides and clusters customers with different life cycles and different business values, has realized commercial landing in the external cooperation of Singularity Cloud CDP. Furthermore, Singularity Cloud can also customize and develop exclusive analysis models for users according to the business characteristics and analysis habits of different enterprises to help enterprises complete the knowledge precipitation and organization improvement of business experience.

policy evaluation

After implementing the business strategy for segmented customers, the marketing department often needs to evaluate its effectiveness and re-offer. For this business scenario, Singularity Cloud CDP incorporates the consumption decision path model. Has the content successfully attracted visitors? The traffic symbols drawn in don't match the target's location? What are the indicators of store entry and purchase conversion? With the application of IOT customer recognition system, Singularity Cloud CDP can analyze the consumption decision path of offline marketing activities that can only be implemented online in the past, helping marketing departments to accurately identify and improve the links that lead to customer churn.

Behind the rise of new retail is the cruel arrival of the post-Internet era. The traffic dividends of various channels have been exhausted, and it often costs high costs to pull new drainage. Up to now, only enterprises that can accurately drain, effectively transform and maximize the value of passenger flow can survive and develop better. As an accurate response to the demand and promote the implementation of enterprise big data business, CDP is coming to us with firm steps.

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