How to maintain personalisation when consumers are talking back to your brand
Challenges of using PURLs and Personalised Data
I recently re-read Paco Underhill’s book ‘Why We Buy – The Science of Shopping’ and was struck by his concern that emerging e-commerce was not demonstrating a key learning from traditional Retail.
The book describes the science Underhill and his team developed around observation in store, which effectively lead to greater insights for store planners and category managers. Add, till data and basket analyses, to Underhill’s structured observation and a whole wealth of in-store behaviour and purchasing decisions opened up. Retailers have been using this kind of data for years to improve store navigation and promote products.
Underhill was concerned that, while it took the Retail Industry 20+ years to amass consumer behaviour intelligence, e-commerce had a very obvious head start and was not using it. In order to transact online consumers were more readily giving data that traditional retailers had to pay for, yet much of the data was sitting untapped in large databases.
Over ten years on from its publication, I think a similar concern exists within the context of how we are communicating with customers across channels. Personalisation has always been key to the success of direct marketing, however today’s consumers are far more marketing savvy and so the personalisation-bar has just been raised.
The benefits of personalisation have long been documented – opening and response rates increase and customers feel more valued as a recognised customer. That was relatively easy to achieve when brands were using direct marketing to broadcast their message. The challenge now comes from the shift from broadcast to dialogue – how do you maintain the personalisation when consumers are talking back to your brand?
Initially you need to keep the personalisation simple and build it up over time as the interaction history with consumers grows. Getting the data strategy correct is essential. Bringing all of the data you hold in relation to customers together is the first step. Customer demographic data, communication history and transactional data should all be used in planning which customers are suitable targets for various campaigns, what the content of the message should be and how much personalisation is available.
The data needs to be segmented based on customer behaviour with your brand (RFM analysis, purchase cycle, web analytics) and response history to previous campaigns. Within each segment there will be insights to drive the content of the message to support the objective of getting the right message to the right customer at the right time.
All going good so far, until we consider the dynamic nature of the dialogue consumer are having with brands. The communication plan and the data strategy driving it need to work across all channels to optimise the customer experience of your brand. Personalisation needs to be executed similarly across channels. Think how it looks to your customers if your direct mail has a high degree of personalisation, but your email has a ‘Dear Customer’ salutation because you could not extract their name from their email address.
Reflect the customers channel preference in campaign selections - both their opt-in/ opt-out status and the channels they have previously responded through. Keep the conversation going by referencing the multi-channel communications you have already sent to the customer. Make sure your direct mail or email also talks about the latest product or service release announced in your recent Newsletter sent to that customer. It shouldn’t feel like each time we are starting the conversation again. Consumers don’t typically distinguish communication disciplines the way marketers do. If we don’t keep an awareness of the communication history present it can lead to a disjointed communication experience.
Integrating channels is the smartest way to deliver all of the content you need your customers to engage with. Use direct mail to raise awareness of your online communications and the benefits of signing up. There is still a higher degree of trust in direct mail and so it should be used together with email campaigns to let customers know about your practises and policies for keeping their data safe, how they can opt out of some or all of your communications.
You need to also manage the frequency of your communications across channel – if you don’t consumers will. Tracking response patterns will establish a tipping point where consumers begin to show fatigue with your communications. This should set the limits for how often you communicate. It doesn’t feel very personal if you keep bombard customers with communication (one fashion chain has emailed me 41 times since April and I still have not engaged. I’m just waiting to see if/when they will ever change their tack with me).
Measurement and analysis to identify what is working is very important. Sales data, campaign response, web analytics, social media monitoring all need to be investigated to learn who responded and why and more to the point who did not. Redirecting marketing spend away from non-responders will increase the campaign ROI and improve the relevance of your communication for your customers.
Back to Underhill’s concern, we have the data, we have consumers who are willing to engage, so how do we achieve credible personalisation in these highly communicative times?
Enough valid, up-to-date, relevant customer data, held in one database to give a single customer view is the starting point. Layer onto this a dynamic communication plan which is cognisant of all the channels including listening to consumer sentiment in social media and you are there. It’s a journey and one well worth planning for!
Got a question for Tara?
Talk to Tara at 086 6020600 or firstname.lastname@example.org
Datalytics is a customer engagement agency that provides clients with access to data expertise and leading edge technology to plan and maximise their most valuable asset – their customer database.