Whether it’s purchase data, on-site browsing data or marketing interactions, ecommerce marketers today have become accustomed to having data thrown at them from many different angles.
This isn’t a bad thing. Data is good. Data is our friend. Data helps us create better customer experiences that drive more revenue.
The problem is that retail data tends to be siloed – stored away in ecommerce platforms, ESPs, social advertising platforms and more. Faced with the prospect of navigating a mountain of CSV files, pivot tables and database SQL queries and – on top of that – making any sense of what you find, the end goal of turning data into a more personalised customer experience can seem very far off.
For many ecommerce marketers, it may not seem worth the hassle. However, in today’s retail climate, do they really have a choice? Considering the fact that over 50% of customers dislike it when brands email information on products, news and offers that don’t match their personal tastes (Ometria Consumer Census, 2016), the answer is a resounding ‘no’.
The reality is, consumers today expect an increasingly personalised experience, especially the younger ones (70% of 18-24 year olds say brands that fail to personalise their marketing will lose them as customers). And that’s not going to change any time soon.
So, instead of pretending it’s possible to deliver effective ecommerce marketing without touching data, it’s time to face the music. What are the key barriers to personalisation, and how can retailers overcome them?
Having a single customer view
As you might already know, the single customer view (also known as a ‘360’ or ‘unified’ customer view) refers to the unification of all of the data you have about a customer – such as their interactions with your site and purchase history – and condensing it into one single record.
Without this complete profile of your brand’s customers and their interactions with your store, how can you expect to send them relevant messages?
As aforementioned, the problem with analysing different sets of data in order to create a single customer view is that data tends to be stored in different places.
Traditionally, marketers would overcome this by, for instance, bringing in a business intelligence team to build a data warehouse, hiring a load of data scientists to make sense of it all, and then attempting to use this insight within the marketing platforms and tools they already have.
But it doesn’t need to be this complicated, time-consuming and costly. There are now ecommerce marketing solutions out there that can take care of this process for you – pulling in customer data from a number of sources, and cleaning and deduplicating it in the process.
These solutions are no longer the reserve of huge retailers with mammoth budgets, but available to almost everyone.
Gaining insight
Another key challenge ecommerce marketers face is using this mass of data to answer key questions, relating to things like retention metrics, customer lifetime value and revenue, and being able to segment this information for customer groups.
This not only enables you to keep an eye on the health of your customer base, but also enables you to derive key actions from your data.
Actioning data
There’s no point having access to important customer information if you can’t turn it into anything that creates value for your business. But what marketing actions can this data power?
Customer lifecycle marketing (CLM) is an approach to customer communication that recognises the fact that different phases of the customer journey require different marketing messages and strategies.
It involves using the information available about each individual customer to create relevant marketing campaigns that will look after them through their journey.
Marketing automation is an important part of customer lifecycle marketing – creating automated messages and campaigns that respond to your customers’ actions, targeting them across different channels like email, social platforms and mobile.
Whether it’s sending a welcome email to a new subscriber to encourage that all-important first purchase, reminding them of an item that was left in their shopping cart or attempting to reactivate old customers that haven’t been around for a while, automated messages improve the customer experience by ensuring they are sent the right message at the right time, based on their behaviour and browsing habits. And they’re completely powered by the single customer view.
Customer data also powers the one-to-one personalisation of marketing messages, ensuring that customers are shown products and content that is relevant to them, based on their customer profile.
In reality, this can take a number of forms: personalised product recommendations in triggered or broadcast emails and across social ad platforms using custom audiences, dynamic content blocks that show different messages to different people based on the kinds of products they’ve shown an interested in, the ability to send marketing messages that only contain discounts for those who need activating (the list goes on).
Case study: Wolf & Badger
Who? One client that uses Ometria’s customer insight and marketing automation platform to send triggered emails, increase repeat rate and engender additional revenue online is luxury online boutique Wolf & Badger.
Why they approached Ometria: The boutique, which offers an eclectic range of products from a host of independent brands, wanted to ensure that its marketing messages were relevant to the needs and interests of each individual customer (instead of sending the same, generic email to its whole contact base).
The solution: Using Ometria, Wolf & Badger set up an automation strategy designed to: re-capture abandoned visits by sending browse abandonment emails; pinpoint ‘at-risk’ and ‘lapsed’ customers using Ometria’s customer lifecycle stage analysis (and reactivate them via automated email campaigns); personalise the post-purchase experience with email campaigns that offer recipients relevant content and personalised product recommendations based on their last order.
The result: After signing up with Ometria, Wolf & Badger experienced a 4% rise in overall online revenue, a 60% increase in repeat rate within 3 months of acquisition (compared to the previous year) and 8x higher open rates on triggered email compared with newsletter opens. Furthermore, £3 was generated for every cart abandonment email sent.
Personalising the overall experience
As well as responding to behavioural patterns, data can also be used to start personalising a customer’s overall experience shopping online.
Bespoke newsletters featuring dynamic product recommendations based on a customer’s likes and dislikes, social media targeting, cross-channel marketing, direct mail and mobile messaging are all part of Ometria’s personalisation service.
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