医药企业在全渠道营销下的内容管理体系——序言

随着行业政策的推动和新兴科技的发展，全渠道营销体系的搭建已成为医药企业在中国市场发展的重要战略举措之一。全渠道营销体系为企业带来更高效、更精准、更敏捷的客户营销模式，从而使企业为客户提供更优质的互动体验。

在营销体系中，内容作为企业与客户互动的终端介质，承接着企业营销策略的落地执行、向客户传递目标信息的任务，直接影响着客户与企业的互动体验。因此，如何建立一个可以成功服务于全渠道特征和目标的内容管理体系是每个医药企业需要思考的问题。

L.E.K. Consulting是L.E.K. Consulting LLC的注册商标。本文档中提及的所有其他产品和品牌均为其各自所有者的财产。
© 2024 L.E.K. Consulting

The Content Management Strategies for Pharmaceutical Companies Navigating Omnichannel Marketing whitepaper series will explore how pharmaceutical companies can realize marketing transformation and modernization by reinventing their content management systems in the artificial intelligence (AI) era. The series will be published in four parts:

Part 1: Customer Centricity
Part 2: Omnichannel Synergy
Part 3: Data and Insights Driven Strategy
Part 4: Agile Process Management

The topics will be discussed in terms of the four “shifts” and cover the following:

Are there criteria for success? What are the specifics?
What is the current status of most companies in the industry? What practices are worth learning from?
What are the main gaps and barriers to implementation?
What are the capability requirements for the organization?

Part 1: From ‘brand-centric’ to ‘customer-centric’

Understanding doctors’ preferences and needs is key to achieving a customer-centric approach. Starting from a comprehensive portrait of doctors, a company can provide an interactive model with personalized engagement timing, touchpoints, frequency and content from the perspective of doctors’ preferences and needs. At the same time, understanding doctors’ preferences and needs can help doctors turn from “passive” into “active” — from passively accepting the information we want to push to actively obtaining the information they want in a timely manner (see Figure 2).

Part 2: From ‘channel isolation’ to ‘channel synergy’

Maintaining consistency, increasing progressiveness’ and satisfying preferences are the key words for the future omnichannel engagement. Omnichannel is not about using ALL channels. Successful omnichannel marketing is more about synergy, i.e., improving the user experience through synergistic multichannel means (see Figure 3).

Part 3: From ‘experience driven’ to ‘data and insight driven’

Real-time, direct access to data is the first step toward insight-driven realization. Real-time data feedback is the starting point for enabling continuous mining of subsequent insights, leading to fast and effective iteration of content marketing plans. Closed-loop omnichannel insights can help pharmaceutical companies answer the question of “how to evaluate the effectiveness of omnichannel” and better establish a direct link between insights and strategy (see Figure 4).

Part 4: From ‘static management’ to ‘agile delivery’

Flexible content management and integrated agile organization are the necessary conditions for companies to achieve content diversification, refinement and personalization under the omnichannel marketing system. By establishing a content COE (center of excellence) to integrate the operational tasks of content management, and by bringing together the cross-functional people involved in the management process, companies can significantly shorten the content production cycle and improve the content quality to quickly meet the changing needs of customers (see Figure 5).

In this white paper, we will also look at the areas where AI and other technologies can be applied to the six key content management processes (see Figure 6), as well as related industry cases.

Content acquisition: Apply semantic analysis and extract classification based on the collected content
Content production: Recognize creative intent and semantic analysis, content retrieval based on the vector database, automatic generation of prompt words and content, conversion of content into different formats and modalities
Content approval: Review content according to the enterprise standard operating procedures
Content optimization: Apply scenario-based embellishment of generated content
Content distribution: Based on the analysis of the customer’s profile and internal content and resource availability, suggest next engagement action and recommend content
Effectiveness forecast: According to the AI placement results analysis, large model outputs effect prediction, effect evaluation report and then reverse optimize the AI placement models