Marketing 5.0 Perspective 1: Being Ahead of the Market – This is How Entrepreneurs and Marketers Do It
Successful entrepreneurs are not dreamers, but rationally intelligence-gathering business leaders.
Data is a marketer’s weapon and guide, helping companies understand consumer psychology. Besides seizing immediate business opportunities and adding value to products, it further solidifies customer loyalty for the next generation and the generation after that. By cultivating a data-driven mindset and mastering Martech, companies can ensure all strategies are supported, analyzed, tracked, and redesigned based on data. This will enable them to build a robust, constantly updated and optimized connection with the market and consumers, laying the foundation for sustainable brand operation.
With consumers spending significantly more time online and shopping, building strong data capabilities and integrating online and offline marketing strategies is crucial for businesses. Marketing guru Philip Kotler’s *Marketing 5.0* identifies two core business strengths: Data Marketing and Agile Marketing , along with three extended applications: Predictive Marketing , Contextual Marketing , and Augmented Marketing. It emphasizes the importance of businesses mastering Martech tools and initiating data transformation . Today, we’ll discuss Data Marketing and Predictive Marketing, explaining why business owners and marketers should definitely study them.
Data Marketing: Understanding Data is a Marketer’s Job
When venturing into data marketing, one must always remember: “Understanding data isn’t just for IT professionals, it’s for marketers.” Entrepreneurs and marketers need to be able to identify the relationships between data points to understand the online activity of potential customers. This allows them to engage with consumers on core business aspects such as product, brand identity, and brand spirit. IT personnel can provide the technology, execute website building and tracking tasks; however, the questions of ” why ” to track data, ” where ” to track it , the relationships between data points and the information they provide , and ” what ” can be done with that information are the brand planning questions that business owners/marketers must consider.
Why is “data marketing” so important? Data marketing is about understanding the market through data collection and interpretation. Over 40% of startups fail quickly, largely because they don’t understand the market. Successful entrepreneurs aren’t dreamers, but rather rational intelligence gatherers. Data marketing has a wide range of applications. We first define the scope and objectives of data collection, then widely deploy data tracking points. The purpose of data marketing, besides determining what product to offer, is to determine “which customer group to target, marketing channels and geographic locations, what industry to invest in, scale, and when to enter/exit the market.” In addition to analyzing the popularity of a product or service, we also study the impact of current events on industry development, designing the entire data marketing process, the scope of data collection, setting clear performance targets, and planning supporting IT equipment, etc.
The new 4Ps of data marketing are interconnected.
Segmenting and analyzing customers lays the data base foundation for targeted marketing. Past theories used the “old 4Ps” to segment the market environment, including macro-environmental factors such as demographics, environment, economy, technology, and socio-cultural factors, as well as individual or group factors influencing marketing (customers, intermediary suppliers, competitors). However, in the era of digital marketing that has broken down geographical barriers, the old 4Ps alone are far from sufficient. We need to add a new “people-centric” 4Ps : People, Performance/Customer Dynamics, Process, and Prediction. People’s online activity patterns are constantly changing. Data collection and the ability to dynamically re-evaluate the 4Ps based on the actions of target groups allow marketing teams to flexibly adjust their target audience and marketing strategies.
New 4P:
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People：
The digital consumer market values individualism, and customers demand a “me-centric” consumption experience. However, the heterogeneity and fluctuating lifestyles of millions of customers necessitate that marketers leverage data to conduct segmented marketing , enabling them to rapidly generate a large volume of customer-oriented services and seize business opportunities.
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Performance/Customer Dynamics:
After initiating the data analysis for the first “People” segment, the next step is to analyze: the effectiveness of our market segmentation and targeted marketing? Did the implemented marketing strategies achieve the expected results, and why? If revenue didn’t improve, what were the key issues? For example, a chain brand might have two branches running the same marketing campaign, but with different results. Analysis might reveal that branch A needs to actively expand brand awareness, while branch B’s primary focus is retaining regular customers. These different needs result in varying appeal of the marketing campaign. Therefore, the marketing direction, strategies, and KPIs for different branches should be tailored to their specific needs.
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Process steps:
The causes of revenue fluctuations are nothing more than: 1. Sales performance, 2. Number of customers, and 3. Average transaction value. When profitability changes (whether for better or worse), the causes of these changes should be systematically filtered through back-end data to identify priority issues or areas for further amplification, and to formulate the next steps to effectively push information back to consumers. Data analysis should be conducted in the process section to fundamentally explore the reasons for changes in numbers. This allows businesses to make immediate decisions and move towards meaningful improvements when profitability is poor ; and when profitability is good, it’s also important to rationally eliminate vanity metrics *1 and focus on things that truly have an impact. Conclusions must be objective so that businesses can consciously extract individual results and accumulate wisdom for brand growth.
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Prediction：
After mastering the first three metrics, businesses can use analytics tools to examine past customer/potential consumer behavior, assess their future product search patterns (e.g., using data to identify families about to give birth and sending them promotional ads for baby products), and the frequency of similar shopping behaviors (e.g., users of Brand A lotion restock approximately every two months), providing marketing recommendations. Data allows us to execute the right personalized marketing at the right time and on the right advertising channels, keeping members engaged and even determining when to abandon a customer and redirect budget to other channels, accurately calculating customer retention costs .
The new 4Ps can be applied during the brand establishment and transformation phases. Utilizing professional data analysis, it helps brands define their marketing direction and ultimately plan their growth trajectory. After defining their products and services, newly established brands first use “People” to identify their target customer group, build user personas, and plan segmented marketing objectives (marketing objectives are not necessarily profit; they can also include increasing brand awareness, improving brand visibility, etc.). Next, “Performance” and “Process” are simultaneously implemented, presenting a rolling update of ” sales, customer acquisition, performance monitoring, variable analysis, continuous calibration of user personas, setting the next marketing objective, and planning customer retention strategies .” This is why relying on data is so crucial; completing such detailed and meticulous work simultaneously is simply impossible by human effort.
Data-driven marketing: Stay ahead of the market and launch your marketing campaign.
An ideal marketing model for a brand can be built upon a foundation of data-driven marketing to predict future product sales results, serving as a crucial reference for corporate operational strategies. We use data to plan Customer Relationship Management (CRM) , quantifying who are the most worthwhile customers to develop/maintain, and calculating the retention period of each customer, so as to concentrate marketing costs on the most suitable targets at present (for example, parents whose children have grown up and have not had another child are no longer considered customers who need to be actively maintained by children’s product manufacturers).
Before consumers are even aware of their behavioral patterns, a proactive approach can identify potential customers, offer them suitable products/marketing solutions, facilitate purchases, and cultivate a loyal customer base – this is the final element of the 4Ps: “Prediction.” A truly sophisticated CRM can integrate “Predictive Marketing” from Marketing 5.0, using AI machine learning to analyze data and predict strategy outcomes before implementation. By anticipating market reactions, businesses can proactively deploy a series of strategies, intervene in market events, and influence consumer opinions.
For small and medium-sized enterprises, it’s unlikely they can drastically change the market and generate hype for their products on their own. However, they can effectively utilize “data-driven CRM” to encourage customers to make purchases and cultivate customer loyalty . For example:
- By training AI to learn autonomously, it can measure customer interest levels in different ad copy and visual combinations, and create ads with high click-through rates and strong persuasiveness. (For example, which emotion is more effective: “Ah! So cute!” or “So touching?”)
- Member segmentation: Members with the highest, second highest, and lowest sales performance/remarketing potential are targeted for segmented remarketing and segmented maintenance.
- By analyzing the performance of marketing campaigns, we can determine the goals and expected profits for the next campaign.
- Product recommendation engines, and how different product ads can be combined to generate benefits (e.g., mobile phone number project ads combined with anti-drop phone case ads).
Businesses leverage data-driven CRM to design meticulous and personalized customer experiences. For example, they can segment potential customers based on advertising placement, ensuring they receive different combinations of ads; or they can provide members with appropriate discount codes based on their preferences. These may seem like small, trivial matters to consumers, but they effectively increase positive memories of products/services, making them essential for brand marketing.
As consumers, we are just individuals, but brands simultaneously face millions of consumers (new customers/potential customers/members, etc.). As mentioned earlier, we cannot handle such a massive workload solely through human intervention. Leveraging data and AI robots allows for rapid growth based on each customer service experience, automatically adjusting how to provide the most suitable service to each consumer next time. In every industry, data is like a wise strategist guiding us to build a strong brand and ensure stable business operations.
Conclusion
Data is a marketer’s weapon and guide. Marketers who understand consumer psychology can not only seize immediate business opportunities, but from a business perspective, effectively conveying brand value to consumers can create premium pricing power, avoid falling into the price war trap, and further solidify customer loyalty for the next generation and the generation after that (e.g., the iPhone). Inventing new products is not the end for a business, but its beginning; solving customer problems and getting more customers back is true success. Establishing a data-driven mindset and mastering Martech, ensuring all strategies are supported, analyzed, tracked, and redesigned by data , will enable businesses to build a robust, constantly updated and optimized connection with the market and consumers, laying the foundation for sustainable brand operation.
- References:
Marketing 5.0: By Philip Kotler, Chen Jiuxue, and Ivan Setiawan
Digital Era: Four Charts to Understand 6 Key Factors for Startup Growth
The Lean Startup: by Eric Rice
- Further Reading:
[Data Application] A Brief Discussion on Digital Marketing & Data Marketing
*1 Vanity Metrics: Proposed in “The Lean Enterprise”. A seemingly outstanding business performance, such as a surge in website traffic, does not actually help understand true performance and can mislead decision-making across departments.
Digit Spark, part of the Zhenhao Internet Media Group, integrates its six sub-brands offering data application services to provide enterprises with comprehensive and precise optimization services across five key areas: “Industry Customer Targeting,” “Performance Optimization Strategies,” “Digital Tool Integration,” “Online Voice Cultivation,” and “Brand Value Promotion.” It drives brand success through data technology.
