The myth of the offline shopper

This 20 minute presentation delivers my thoughts and experiences on the myth of the offline shopper. Do they actually exist? And if so how do we communicate with them in a digital world?

This presentation was originally produced and delivered by myself at Drink Digital in Nottingham on 25th May 2017 in Suede Bar. Drink Digital aims to “bring the East Midlands digital marketing community together”. It’s a talking shop for anyone involved in digital – SEO, PPC, social, email, CRO, design, content and affiliates.

Topics include persona marketing, the customer experience, multi-channel marketing & attribution modeling.

Introducing the offline shopper

I’ve got a pet peeve (Slide 3). It’s businesses saying they’re “an offline business”. It’s people saying they “don’t really shop online”. In modern marketing gone are the single-instance purchases, replaced instead with multi-channel, micro-moment strategies.

Through the remaining 20 slides I’ll argue that in 2017 there is no such thing as an “offline shopper”. Put another way, I firmly believe that online has a profound and fundamental impact on every business, even if you don’t (directly) sell your products or services online.

Part 1: Who is the offline shopper?

The first thing any marketing team needs to do is identify their offline shopper personas. Ideally, this should use existing customer insights (from your CRM database) to identify those customers who are less comfortable with technology. Take all of your personas (if you don’t already have a handful, create them) and map them against a simple technology familiarity scale (slide 6, Technophobe vs Technophile).

Truly understand your personas

When mapping your personas against technology familiarity, it’s important to look deeper within each individual persona. Age, whilst an initial indicator, should never be the only point of reference for technology familiarity. Facebook’s 55+ demographic is actually the fastest growing group (slide 7), so don’t just presume that old = technophobe and young = technophile.

For this presentation, I’ve used three example personas; Hannah, Tina and Pete (slide 8). Each has their own technology problems – From needing to try things on to security concerns. It’s important that you know the hesitation of each persona to shop online as they won’t all be the same.

Part 2: What is the shopper journey?

Let’s go back a step. Remember the person who said they don’t shop online? Or the business who said their shoppers are all offline? They’re only seeing the step (the physical purchase) of what is likely a much longer journey. I’ve called this the “uninitiated’s view” (Slide 10). What’s much more likely is that there have been a number of interactions, or moments, which have lead to the final purchase. These can be both online and offline, across multiple channels and take an unspecified amount of time.

By revealing the whole customer journey (from awareness to purchase) we open a new question… Which channels contributed the most to the sale? We’ll get into attribution modeling a little later!

Creating a micro-moment strategy

Micro-moments are something that Google have been focusing on for some time now. You can find out much more about micro-moments over at ThinkWithGoogle, but in a nut-shell (slide 11)…

“Mobile has fractured the consumer journey into hundreds of real-time, intent-driven micro-moments. Each one is a critical opportunity for brands to shape our decisions and preferences.”

Creating a micro-moment strategy requires four key steps (Slide 12):

  1. Make a map of moments you want to win.
  2. Define the needs during those moments.
  3. Understand how you can create a personalized experience for that moment.
  4. Ensure you’re there, quick and useful for each moment.

Once you’ve answered these questions for each persona you can begin executing your own segmented micro-moment strategy!

Part 3: How can we talk with offline shoppers?

So we know that our technophobe personas prefer to purchase offline. What we also know (thanks to Google) is that 87% of customers research online before purchasing in store (slide 14). This is known as webrooming – Browsing online but buying in store. Webrooming has driven two key stats over the last 5 years:A 57% decrease in footfall as less people

  • A 57% decrease in footfall as less people visit stores in ‘browse mode’
  • A 300% increase in conversion rate in stores, as people visit in ‘purcahse mode’

Effectively changing consumer behavior, driven by mobile, has lead to stores shifting position from the awareness and consideration phases of a customer journey towards a purchase-focused channel.

We need to address this in two ways. First, create a multi-channel strategy (Slide 15) which includes three key elements at it’s core;

  1. Inputs – Customer insights are key here (personas, CRM data, etc).
  2. Test & Learn – Getting the most out of channels which work for your customers.
  3. Outputs – A seamless customer experience which surprises & delights, ultimately generating sales and (importantly) loyalty.

But which channels should we focus on? After all, there’s a fair few to choose from and each has it’s own advantages. Ultimately, we need to select the channels which the customers prefer at each phase of their lifecycle (Slide 16). Each phase of the customer journey needs to be seamless with the next, and each needs customer insight in order to execute a true fail-fast, data-driven approach.

Part 4: Measuring performance

As marketers we put a huge amount of time, money and resource into getting channels performing to their best potential (read; Max ROI). But there’s an industry-wide misalignment between investment and customer habits (Slide 18). We know (again via Google) that there’s an over-indexing of investment for TV advertising compared to the amount of consumer’s time spend watching TV. The reverse is true of digital, which is significantly under-resourced compared to time spent.

So how do we address this? The answer is with smarter attribution modeling.

There are a few different attribution models accessible in Google Analytics. Last click is default but there’s also first click, time decay and position based. They each have their own way of measuring channel performance (Slide 19).

Whilst data-driven attribution modeling is great, it’s not easily accessible to many businesses. Ultimately each business needs to identify their preferred method of attribution, and for me it’s a combination of time decay and position based (Slide 20).

What about ‘The extreme technophobe’?

There’s an elephant in the room, here. Each of the personas described previously (Hannah, Tina & Pete) each have an internet connection. What about a persona who doesn’t have a connection, a mobile or a TV? Let’s call her Marge, an 87 year-old grandma who lives in a ‘digital cave’ (Slide 22). Can she possibly shop online? Can online have an impact on her shopping habits? Or is she truly an offline shopper?

The answer, I’d argue, is that even Marge is influenced through online. Just perhaps not as directly as others. The reason is that Marge has influencers, just like everyone else. In Marge’s case this may be her 8 grand-daughters (Slide 22). Her grand-daughters shop online, and are influenced by what they see. They’re likely, in some way, to influence Marge. And in an extreme case Marge may even ask her grand-daughters to buy things for her… Which they MAY do online!

The takeaway points

  • Use persona marketing to understand customer needs and the reasons they prefer to make purchases offline.
  • Create a data-driven, multi-channel and micro-marketing strategy.
  • Focus on customer intent and select channels which create a seamless experience.
  • Ensure your investment reflects your persona habits by analyzing performance.


I’d love to hear your thoughts, questions, and opinions on offline shoppers, and a massive Thank You to Boom Online for inviting me to present, as well as everyone who listened and spoke to me afterwards!

John Alexander Rowley

An enthusiastic digital marketing professional passionately dedicated to increasing the online presence of businesses and individuals in order to improve engagement and ROI.

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