[Guest post] Touching Your Customers Appropriately – Customer Engagement in the age of Big Data大数据,大互动

By Theresa Clifford Director, Customer Engagement at Cucumber.

Using Big Data to increase Customer Engagement

Back in 1870 John Wanamaker, the father of retail, remarked: Half of what we spend on marketing is wasted – the problem is we do not know which half. During tough economic conditions, we can’t afford to blow half our budget. Increasingly budgets are being questioned and hard metrics are being asked for. ROI is now more and more at the forefront of everyone’s minds.
However a number of studies show that measuring ROI is a major challenge for many organisations:

  • 47% of companies were not able to measure the value gained from marketing
  • Only 44% of CMOs feel fully prepared to be held accountable for marketing ROI
  • 57% of companies are not basing their marketing budgets on any ROI analysis
  • And over 30% of companies base their marketing budgets on historical spending and simply gut instinct

The Good News

The good news is that with the rise of new and easily measurable technologies and channels such as mobile devices and social media, we now have the potential to dramatically improve our levels of customer engagement and can take a lot of the guesswork out of budget decisions. .
We are now capturing a massive amount of structured and unstructured data. And the need to understand this data is top of the agenda. The information we now receive on customer transactions, loyalty programmes, likes, dislikes, and preferences could really give us a very deep level of customer intelligence. 

The Bad News

But recent research by Columbia Business School shows that we are currently wasting this potential. They found that:

  • 42% of marketers are not able to link their customer data at the level of an individual customer
  • nearly half are not using data to personalise their marketing communications
  • 28% still do not know which high-value customers to focus their marketing on
  • two in five marketers cannot turn that data into actionable insight
  • and 51% are not using the data they are collecting at all

It is clear that many marketers are feeling overwhelmed with the amount of data they are receiving. The IBM CMO Survey for 2012 found that 65% of CMOs are unprepared for the growth of data from mobile and social media.

Ask the right questions

The challenge for making the most of all this Big Data is to turn it from a mass of data into real business insight.  And in order to gain these insights we need to ask the right questions.  
So we need to ask questions around the What, Who and When…….
What insight can we derive from the information that we’ve captured?
Who needs to know this information?
And when do they need to know in order to make a more informed decision?

Getting started on Big Data requires the following steps:

  • Define your business objectives and goals
  • Know your data – is it clean? Is it up to date?
  • Know what data you need to collect and what you want to measure
  • And when you start modelling – make sure you use an expert!
  • Then deploy and evaluate

Predictive Analytics can help us understand Big Data and is becoming crucial to customer engagement today. Whereas data analysis has typically had an ‘historic’ focus, Predictive Analysis allows us to predict future trends and behaviour patterns and identify where our best opportunities for customer engagement are going to be in the future.

Right Touching

Big data and Predictive Analytics can play an important role in helping us to Right Touch our customers. Right Touching is all about touching people in the right way, at the right time, with the right content, on the right channel.  But in order to get this right, you have to know your audience.
So how do you make sure you are right touching? Some key questions to think about are:

  1. Where are your customers online?
  2. What devices do they use?
  3. When do they use these devices?
  4. What do they do online?
  5. And what do they want from you online?

For example, the Financial Times has looked into what devices its customers prefer to use during the course of the day. The tendency is to use mobile in the morning, desktop during the day while at works and tablets in the evening while watching TV. And they adjusted their campaigns accordingly.

Let Big Data be your friend!

We shouldn’t be scared or feel overwhelmed by Big Data. Big Data and Predictive Analytics can help us identify our best engagement opportunities. Through these insights we can then deliver real relevancy to our most valuable customers and further increase their loyalty. But it requires that you ask the right questions to ensure you deliver relevant and meaningful engagements and that you monitor and measure the hard and soft metrics to hone your offering.  

Theresa Clifford is Director, Customer Engagement at Cucumber. This blog post is an extract from the speech she is giving in Melbourne for the Sitecore Symposium in October 2012.

 1870年,“百货商店之父” John Wanamaker留下了堪称广告营销界的“哥德巴赫猜想”的一段话,“我知道在广告上的投资有一半是无用的,但问题是我不知道是哪一半”。尤其是在经济萧条时期,巨额的广告费用让许多广告商头疼不已,除此之外,广告投入的回报率也同样另企业手足无措。回到现在,投资回报率(ROI)的概念已经深入人心,但是数据显示,评估ROI始终困扰着大多数的企业:

  • 47% 的企业无法评估市场营销带来的价值。
  • 仅有44% 的首席营销官为市场营销的ROI评估承担责任。
  • 57%企业的市场营销预算没有建立在ROI分析的基础上。
  • 超过30%企业仅仅通过以往市场营销经验或直觉设立市场营销预算。






  • 42% 市场营销人员无法将客户信息精确到个人。
  • 近一半的市场营销人员不使用数据进行有效的销售信息交流。
  • 28%市场营销人员不知道谁是他们的高价值客户。
  • 五分之二的营销人员不知道如何将数据转化为最终销量。
  • 51%市场营销人员只收集数据却从不使用这些数据。


1. 我们能从收集的大量信息中得出的结论是什么?
2. 谁应该了解这些信息?
3. 我们什么时候应该了解这些信息以便做出明智的决定?


  • 确立企业的方针和目标
  • 明确你的数据(是否清楚明了?是否与时俱进?)
  • 明确你需要收集什么样的信息和如何评估这些信息
  • 确保你拥有专业人士在合适的时间给出分析结果
  • 应用数据并且评估效果

预测分析(Predictive analytics)可以帮助我们更好的理解大数据带来的影响,从而帮助我们在今天能够更好的与客户互动。尽管,我们得到的数据普遍具有“历史性”,但预测分析却可以使我们以史明鉴展望未来。


大数据和预测分析均能帮助我们正确接触我们的客户。正确接触(Right Touch)意味着使用正确的方法,在正确的时间,用正确的内容接触到正确的人。为了实现“正确接触”,你首先需要了解谁才是你的受众。先明确几个问题吧:
1. 你的潜在客户平常出现在哪些网站?
2. 他们使用什么工具上网?
3. 他们什么时间使用这些工具上网?
4. 他们在网上干什么?
5. 他们在网上对你的企业的需求是什么?




Theresa Clifford 是新西兰Cucumber公司客户互动部门总监。2012年10月,Theresa在澳大利亚墨尔本举行的Sitecore Symposium会议上发表了关于“大数据和大互动”的演讲,本篇博客根据其演讲内容进行整理。

Leave a comment

Your email address will not be published. Required fields are marked *