So many demand gen tools. Of course, a CDP's there.
I've been working on a post related to e-commerce and, in particular, Shopify stores for a while. Understanding the phenomenon of e-commerce and how demand generation has changed with influencers and social media is intriguing. Of course, there's technology at the center of the story. Some Shopify stores have robust marketing tech stacks. In this post, I'll discuss four ways a customer data platform (CDP) can amplify the demand generation strategies you're making for your Shopify store. A CDP can certainly help bring in more sales with all its features focused on activating customer data.
Briefly, how CDP software works in your marketing stack
I refer to a marketing stack as the set of applications and tools you need to nurture and engage your customer for sales. For example, a typical marketing stack I see of medium-sized businesses includes Facebook Ads, Shopify, Mailchimp for email nurturing, Google Analytics, Facebook Messenger. Adding off-line data regarding influencer commissions needs to be done for reporting too. If you can put data at the center of your demand generation activity and let it drive the decision-making and tactics, then a CDP becomes a central component of your engine.
The CDP Institute often sites the core characteristics of a CDP to 1. Pull data from multiple sources 2. Clean and combine data into individual profiles, and 3—the data structure for other marketing systems to use. In looking at what Shopify store owners have been doing and handling, these marketing teams can easily use a dozen applications. Customers expecting more and using more devices, the channels, and means to grow demand often drives the investment in so many marketing solutions. Everyone requires the right combination of technologies to deliver the best customer experience these days.
Data fragmentation occurs when customer data gets siloed into different applications. This fragmentation leads to a CDP first challenge, connect the pieces and delivers a single customer view. Not to put too fine a pint, but this particular challenge is enormously hard and can take time. The data needs to be clean, formatted, understood in its context. Identity management is how we organize individuals into profiles.
And once you have the profiles, the data is unlocked to produce all the exciting marketing value of effective demand generation. In this post series on Shopify store marketing stacks and a CDP, I cover:
Engage customer segments with their own journeys
Find opportunities to shorten the checkout process
Generate better social posts and ads
Analyze content performance on CX
Engage customer segments with their own journeys
Even for fast-moving sales related to Shopify stores, it's still important to actively engage customers. The engagement flows are what become different customer journeys. I find that emails again become an effective strategy because you can set up a series of automated and rule-based flows. Emails also provide an excellent medium for personalized messages- software for email automation has come a long way. Videos like video tutorials and case studies also offer much-personalized engagement for customers, especially on mobile devices.
With your order data, you can start to distill even more advanced customer segments using a CDP. A CDP can bring in information, not just behavioral data from your email systems, but also add psychographic data from surveys and lead generation forms. Media usage and consumption would also be fascinating to investigate when defining valued segments for Shopify.
Customer journey analytics is also a CDP benefit, albeit a very challenging solution to go after. When customer's data is coming on different applications but over the same customer journey, data fragmentation and the gaps become harder to fill. Markers will often complain about having a messy funnel. It's the same problem that needs Identity Management and Contextualization. Both are robust features of CDPs and what makes it possible to evaluate what's going on in a multi-channel customer journey.
Find opportunities to fine-tune the checkout process.
The general rule of thumb in customer experience (CX) is that the less customer effort, the better the throughput. Customer effort works like friction in the buyer journey. But uncovering the right tactics that don’t turn off your customer segments in streamlining will be necessary.
When discussing solutions for contactless customer journeys at the beginning of the COVID-19 re-opening, I mention many tools that streamline the order and payment process that enhance the overall CX while offering digital channels preferred by their target customers. You often hear marketers and customer experience experts refer to this as the multi-touch multi-channel customer experience. Products and services that require consideration have more complex business journeys. That's not to say a Shopify experience does not also stand to gain efficiencies in the checkout process.
The e-commerce and Shopify world thrive on the contactless world. Designing intuitive order flows that include customizations and personalized orders does tend to open a can of worms for marketers when analyzing downstream. But analyzing the products that move the best against your most valued customer segments allows you to consider the menu and ordering process and the overall product mix. When screen space is so valuable, it is important to have just the right amount to offer.
Product recommendation engines for upselling and cross-selling can give you a lot of insight and move against what customer segments. This insight into customer segments will inform the kinds of customer journeys you need and the type of payment technologies your customer segments are willing to utilize. Millennial customer segments are ready to make mobile payments like Google pay, which integrates well within Shopify. But not all segments feel there is enough security around such a quick payment solution and will purchase more to have a couple of secure steps or features. Millennials may get the bulk of Shopify’s attention, but your primary segment for a store on this platform should be considered based on what you are selling.
With the sales information, cross-referenced against audience profiles, plus engagement data, a CDP can begin to distill organic customer segments organically. At VIEWN, we are taking machine learning approaches to evaluate the real characteristics that drive customer segments. The CDP segments can inform you about payment solution trade-offs and test assumptions around product mix- key attributes when looking to shorten the sales cycle.
Hang on for Part 2 of this series of CDP amplified Shopify strategies where I go into
Engage customer segments with their own journeys
Find opportunities to shorten the checkout process.
Generate better social posts and ads
Analyze content performance on CX
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