京公网安备 11010802034615号
经营许可证编号:京B2-20210330
大数据与数字化营销
【大数据与数字化营销】据对美公司首席信息官(CIO)的调查发现:仅23%的公司在收集顾客的人口信息和消费习惯之类的数据,并且利用这些数据进行战略决策。但其中却仅有46%的公司拥有数据分析的资源或系统。他们面对的主要挑战在于数据处理、信息管理和数据分析难题。数据管理平台(DMP)发展空间巨大,将是未来数字营销的理想工具。
文章全文:
To Handle Big Data, Advertisers Turn to DMPs
There’s a big to-do about Big Data and data management platforms (DMPs) in the digital advertising space. According to a new eMarketer report, “Data Management Platforms: Using Big Data to Power Marketing Performance,” DMPs enable marketers to use their Big Data to make smarter and more efficient marketing decisions.
Still even as brands use Big Data to build a holistic picture of their potential and real customers, many still find it challenging to extract cross-channel insight from that data.
Ziff Davis found 49% of companies polled worldwide had enacted a data management strategy as of fall 2012. And according to a survey from IT staffing service Robert Half Technology, just 23% of US chief information officers (CIOs) said they were collecting customer data such as demographic information or buying habits. Of that small percentage, less than half (46%) reported having the resources or systems to analyze the information they gathered.
A very general term, Big Data can refer to first-party customer information, third-party audience data, offline purchase data, online advertising behavioral data, campaign analytics and much more.
It can prove challenging to integrate disparate sets of data coming from social media, campaign analytics, offline sources or third parties. In fact, Big Data solution provider Infochimps surveyed IT professionals in North America and found that 83% of respondents said processing such information was a leading Big Data challenge, followed by managing the information (42%) and analyzing the data (41%).
If data is digital marketing’s currency, then the DMP is its bank. Big Data is stored and standardized here so that each data asset can be tied to a particular customer or audience segment. Once standardized, marketers can use that information to power multiple functions, both within digital and across a company’s broader marketing program.
DMPs can house both structured data, typically quantitative in nature, as well as unstructured data, often qualitative in nature—for example, social network data. Once all of these disparate sources are entered, DMPs can standardize them to build a larger, more descriptive picture of a customer or audience base that marketers can act on.
The DMP’s ability to take all of that Big Data from first-, second- and third-party sources and then organize it into meaningful audience segments makes it an ideal tool for audience targeting. This function—particularly for first- and third-party data—was also the top-reported competency of DMPs by US marketing professionals in a September 2012 surveyed by Winterberry Group.
Other than their role in organizing data on customers, DMPs are also a prime tool for campaign measurement, both within digital and across platforms.
“There’s real value in being able to address the audience first to determine what to buy,” said Mark Zagorski, CEO of data provider eXelate. “By looking at your audience and how they’re interacting with a particular ad or promotion, you can take those learnings and feed them into your current efforts and your next campaign.”
The full report, “Data Management Platforms: Using Big Data to Power Marketing Performance” also answers these key questions:
数据分析咨询请扫描二维码
若不方便扫码,搜微信号:CDAshujufenxi
机器学习的本质,是让模型通过对数据的学习,自主挖掘规律、实现预测与决策,而这一过程的核心驱动力,并非单一参数的独立作用, ...
2026-03-27在SQL Server数据库操作中,日期时间处理是高频核心需求——无论是报表统计中的日期格式化、数据筛选时的日期类型匹配,还是业务 ...
2026-03-27在CDA(Certified Data Analyst)数据分析师的能力体系与职场实操中,高维数据处理是高频且核心的痛点——随着业务场景的复杂化 ...
2026-03-27在机器学习建模与数据分析实战中,特征维度爆炸、冗余信息干扰、模型泛化能力差是高频痛点。面对用户画像、企业经营、医疗检测、 ...
2026-03-26在这个数据无处不在的时代,数据分析能力已不再是数据从业者的专属技能,而是成为了职场人、管理者、创业者乃至个人发展的核心竞 ...
2026-03-26在CDA(Certified Data Analyst)数据分析师的能力体系中,线性回归是连接描述性统计与预测性分析的关键桥梁,也是CDA二级认证的 ...
2026-03-26在数据分析、市场研究、用户画像构建、学术研究等场景中,我们常常会遇到多维度、多指标的数据难题:比如调研用户消费行为时,收 ...
2026-03-25在流量红利见顶、获客成本持续攀升的当下,营销正从“广撒网”的经验主义,转向“精耕细作”的数据驱动主义。数据不再是营销的辅 ...
2026-03-25在CDA(Certified Data Analyst)数据分析师的全流程工作中,无论是前期的数据探索、影响因素排查,还是中期的特征筛选、模型搭 ...
2026-03-25在当下数据驱动决策的职场环境中,A/B测试早已成为互联网产品、运营、营销乃至产品迭代优化的核心手段,小到一个按钮的颜色、文 ...
2026-03-24在统计学数据分析中,尤其是分类数据的分析场景里,卡方检验和显著性检验是两个高频出现的概念,很多初学者甚至有一定统计基础的 ...
2026-03-24在CDA(Certified Data Analyst)数据分析师的日常业务分析与统计建模工作中,多组数据差异对比是高频且核心的分析场景。比如验 ...
2026-03-24日常用Excel做数据管理、台账维护、报表整理时,添加备注列是高频操作——用来标注异常、说明业务背景、记录处理进度、补充关键 ...
2026-03-23作为业内主流的自助式数据可视化工具,Tableau凭借拖拽式操作、强大的数据联动能力、灵活的仪表板搭建,成为数据分析师、业务人 ...
2026-03-23在CDA(Certified Data Analyst)数据分析师的日常工作与认证考核中,分类变量的关联分析是高频核心场景。用户性别是否影响商品 ...
2026-03-23在数据工作的全流程中,数据清洗是最基础、最耗时,同时也是最关键的核心环节,无论后续是做常规数据分析、可视化报表,还是开展 ...
2026-03-20在大数据与数据驱动决策的当下,“数据分析”与“数据挖掘”是高频出现的两个核心概念,也是很多职场人、入门学习者容易混淆的术 ...
2026-03-20在CDA(Certified Data Analyst)数据分析师的全流程工作闭环中,统计制图是连接严谨统计分析与高效业务沟通的关键纽带,更是CDA ...
2026-03-20在MySQL数据库优化中,分区表是处理海量数据的核心手段——通过将大表按分区键(如时间、地域、ID范围)分割为多个独立的小分区 ...
2026-03-19在商业智能与数据可视化领域,同比、环比增长率是分析数据变化趋势的核心指标——同比(YoY)聚焦“长期趋势”,通过当前周期与 ...
2026-03-19