Data & 数字服务 数字进化 数据分析

Traditional syndicated data is aggregated market data that’s collected by market research firms and sold to businesses with an interest in that market.

例如, a retail brand might purchase and use aggregated behavioral data by Zip code to plan geographically targeted promotions.

零售 and consumer product goods (CPG) companies have been using syndicated data for years, 但直到最近, 只有大公司才有能力这样做. 现在, 多亏了科技的进步, middle market companies can afford to start using syndicated data in their data analytics strategies for better, 更明智的预测和计划.

One reason to consider using syndicated data is that the boundaries of what’s possible with data are expanding. Not only is it now easier and more affordable for smaller companies to use syndicated data, 但是更多类型的联合数据正在变得可用. 例如, syndicated data is being used to predict broader climate change and how that will impact crop yield, 水分分配和其他影响农业规划的因素.

Another change is that the data is more meaningful because it’s now generally available in near real-time. So, instead of evaluating how a promotional program worked 12 weeks after it ended, a company can track near real-time sentiment of its brand and products using syndicated social data.


在过去, 数据分析需要昂贵的招聘费用, highly skilled professionals who would use time- and resource-intensive processes to analyze data. 今天, cloud platforms such as 微软 Dynamics 365 include tools that automate data analytics for business users. This puts the ability to use syndicated data for data analytics into any user’s hands.

同时, other advances—such as high-speed networks and application program interfaces (APIs)—have made it easier for new groups to offer syndicated data, 这些传统上只来自少数几家占主导地位的公司.

But as technology continues to evolve and the amount of data generated grows exponentially, there’s nothing that limits any type of third-party data from being syndicated or how businesses use that syndicated data for 更明智的预测和计划.


  1. 领先指标:有时联合数据用于长期规划, 但它也可以用于短期预测和规划. 在大流行危机期间, 例如, 敏捷性至关重要, so retailers used syndicated data of econometric factors as leading indicators for forecasting which products and product mixes to offer three, 6到12个月.
  2. 智能预测: Adding syndicated data to existing data sets can provide enough data to use machine learning (ML) models for more intelligent forecasts or to improve the efficacy of existing ML models. 当智能数据模型得到更广泛的信号时, 由此产生的见解更受数据驱动,更具有预测性.
  3. 选址及容量规划: For capital-intensive companies such as industrials and retail store chains, 联合数据可以提供额外的信号,说明需求将在哪里, as well as where necessary resources—such as employees with the right skills—are more likely to be. This can be particularly important as remote work becomes more common and as more weather-related events unexpectedly disrupt operations and supply chains.
  4. 测试模型和假设: One of the risks of using data analytics is having a biased model because that could make the resulting analysis incomplete or skewed. Using third-party data sets to test the model could help teams identify bias and make adjustments. 当添加联合数据时,如果一个指标明显不同, 对于instane, 这可能是一种偏见的迹象.

同样地, syndicated data could be used for additional risk-testing of any assumption, 比如有计划的交易的投资理论. 在尽职调查阶段, syndicated data can add context and shed light on overlooked factors that should be considered for testing.

  1. 探索: 《vwin德赢娱乐》 估计创建的数据量, 捕获, 世界上的复制和消费增长了5%,从2010年到2020年. 有迹象表明,这一速度正在加快, and technology for performing data analytics is becoming even faster and easier to use. We are living in a golden age of unearthing new knowledge because of these trends, and part of any data analytics strategy should be to grow organizational knowledge and opportunities.

Syndicated data can be an essential part of this exploration on the tactical level. Perhaps a team is considering five common behavioral factors to model scenarios about product preferences. 当他们加上之前没有考虑过的六分之一时会发生什么? They could discover a new indicator that proves beneficial in predicting preference and even influencing strategy.


Having a strong data infrastructure is the baseline for effectively adding syndicated data to your data analytics strategy. 尽管现代应用程序使执行数据分析变得更容易, 这些只是有效数据策略的一部分.

能安全地吸收的, 与合适的人管理和共享联合数据也很重要, 而这些任务通常落在组织的肩上. 对于许多中端vwin娱乐场官方公司来说,这可能是一个沉重的负担, so some choose to partner with business and technology consultants such as RSM to help them design and deploy an effective data strategy, 或者他们使用顾问的托管服务来帮助处理工作负载.

现在’s a good time to review your data infrastructure and data analytics strategy to determine whether your organization is prepared to take advantage of all the benefits of using syndicated data.