To find out, Econsultancy invited dozens of client-side marketers in Shanghai to discuss this and other topics at roundtables in April of this year.
The roundtables were moderated by volunteer client-side marketers and subject matter experts from Econsultancy and our event sponsor Epsilon.
Below is a summary of the main talking points during the day about the topic: Data-Driven Marketing – Making Big Data Actionable.
Managing customer data
Delegates at the table decided that there are three aspects to managing customer data:
- Understanding marketing data
- Realising insights from the data
- Making decisions using the data
Below are summaries of the discussion around each of these aspects.
Participants said that in order to manage customer data, marketers first need to agree on the data needed to achieve marketing goals.
Then, once there is agreement, everyone must understand the data sources and their limitations.
The first challenge, noted one attendee, was that there are no standardized measures or metrics for different touchpoints.
Marketers can get data from a variety of, say, display touchpoints and each will have its own interpretation of what a ‘view’ is or even a ‘click’.
Another problem marketers face when understanding data is that each department has different benchmarks and so it is difficult to establish key performance indicators (KPIs). This is especially true with companies which have many brands and a single marketing department.
Finally, one participant noted, that his team struggled to convince the company of the commercial value of data-driven marketing. The systems required to capture, store, and manage data were expensive when compared with the overall cost of marketing.
Delegates noted that quantitative data, such as views, clicks, and conversions, is the most important data to marketers for now, but looking ahead they agreed that qualitative data will become more important.
Data sources such as surveys, focus groups, and Net Promoter Score are starting to emerge as a way for brands to record data about how people are reacting to content and marketing strategies.
Once marketers have the data, participants agreed that the next part of making big data actionable is to organize and interpret it.
Discussions on the day focused on three key data sets used by participants:
- Social metrics: Followers, fans, likes, shares, and comments
- Web metrics: Page visitors, unique visitors, average page depth
- Ecommerce metrics: Customer purchase behaviour
Organizing customer data into these categories helped marketers from even the largest brands start the process of making their big data actionable.
Social data showed how their messaging was performing against other brands.
Web metrics help with determining whether they were delivering a high-quality customer experience. And ecommerce metrics were necessary to report on performance to management.
Attendees indicated that marketers in China faced some unique challenges when trying to realise insights from their data. Here are a few that were mentioned:
- Data Management Platforms (DMPs) are unreliable. Other countries are able to use external data from DMPs to enhance their internal data, but most participants felt that DMP data in China was not reliable.
- Cleaning data is expensive. When third-party data was available, attendees felt that it was time consuming and resource intensive to clean and verify it.
- WeChat data is sparse. Many brands use WeChat in China for delivering content, but the channel does not provide insightful data about the people who view the content.
- Third party sites own ecommerce. In China, a lot of ecommerce traffic involves one of the main ecommerce sites (TMall, JD). Because of this, it is hard to get full access to customer data.
Participants decided that when trying to tackle ‘big data’, it was best to start with small projects which deliver quicker results.
Some examples provided were:
- Use website data to map out and better understand the customer journey.
- Use social data to understand how individual campaigns affect fan and follower numbers.
- Track customer loyalty with transaction history and other CRM data.
Finally, attendees discussed how they make decisions from the data that they have collected and organized.
Some examples provided were
- Collating customer profiles using website data, presenting customized homepages for segments, and delivering personalized content.
- Ensuring customers get a marketing message at the right frequency. Not so infrequent that they don’t see it, but not too much that they become annoyed with the brand.
- Monitoring real-time feedback, such as social media and customer reviews, to make sure customers understand the brand message.
In order to use customer data to make marketing decisions, marketers must become very familiar with compliance and policies in China.
It is difficult to re-use customer data on most digital platforms in China. They are not designed for things like Facebook custom audiences.
B2B marketers still rely on industry data and third party analytics because their customers are often middlemen such as resellers and distributors.
Participants indicated that they would like to make better decisions based on the data they have about consumer behavior.
Few, however, felt that the data required to do so was easily available. And, once they did have the data, a lot of effort had to go into cleaning and verifying the data before using it to make decisions.
But there is hope. Participants agreed that qualitative data, such as emotional impact and engagement with campaigns, will help marketers decide which campaigns are truly meaningful to customers.
A word of thanks
Econsultancy would like to thank all of the client-side marketers who participated on the day and our sponsor for the event, Epsilon.
We would like to extend a special thanks to the table moderator for this topic, Louise Au, Co-founder & Partner at Axis Business Consulting.
We appreciate all of the helpful discussion points participants provided on the day and we hope to see you all at our upcoming Econsultancy events!