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How Data is Defining Your Customer's Journey

Combining data analytics with marketing means you need to determine how best to apply your collected customer data to the customer journey. But what is the customer journey?

The Customer Journey

HubSpot, a marketing and sales software developer, defines the customer journey as “the process buyers go through to become aware of, consider and evaluate, and decide to purchase a new product or service.”

In other words, the customer journey consists of the steps leading up to a purchase decision, regardless of scale.

This process begins with a realized need: the customer initially identifies that there is a problem that needs to be addressed. It could be a family preparing for a third child and coming to find that they won’t be able to fit three car seats in the back of their sedan. It could be a person who is cooking dinner at home one night when the handle breaks off of the saucepan. Or it could be a corporation learning that its content management system is outdated and lacks critical security features. This is called the awareness stage.

Once prospects are in the awareness stage, they start to move forward in the customer journey, to the consideration stage. In this stage, customers understand the problem they need to address and start to research how to solve it. To continue the earlier example of the broken saucepan, maybe that individual — let’s call her Karin — starts to weigh her options.

Karin has a number of choices, including continuing to use her broken saucepan, buying an inexpensive replacement or buying a high-quality pan. To help with her decision, Karin might read some online reviews, talk to friends and seek their opinions or even go to a cookware store and speak with an employee.

Once Karin knows she wants to buy a high-quality saucepan to replace her broken one, she transitions to the decision stage. In the decision stage, Karin will do more research — online or in-person — to decide what pan she wants to buy and where she wants to get it. Which manufacturer has the best warranty? Which pans are the highest rated? What material does she want it to be? And once she chooses her saucepan, where is the best (cheapest? most convenient?) place for her to buy it?

Why Is the Customer Journey Important?

Even in a situation as simple as this, there are many factors at play, and a company selling saucepans can have a lot of potential data sources to learn from and seek to engage Karin through. Her browsing history, time spent researching on the company’s website and even social media posts can help build a customer profile.

If your company has potential customers trying to find information about specific products to make informed purchase decisions, it is in your best interests to educate those prospects as much as possible. If you are able to anticipate your customers’ needs along their journey to a purchase, you are much more likely to create valuable engagement and convert leads to sales.

To do that, you need to be able to understand your potential customers. What problems do your products and services solve? How can you present your offerings as solutions to prospects’ needs? What kinds of questions are your prospects asking, and where are they looking for answers?

When your customers are on a journey, they want information, not a salesperson. They’re looking for signposts, directions, a map. They want to find a guide they can trust who will lead them to a satisfying decision.

And if you can effectively use data analytics, you can be their guide.

Evaluating the Customer Journey Through Data

As noted above, successfully engaging with prospects along the customer journey means anticipating their needs and knowing what they’re looking for, as well as where they’re looking for it (such as knowing that around 70% of prospects turn to Google for research during the awareness and consideration stages).

If you know where your prospects are looking for information (Google, social media, online and brick-and-mortar retailers), you can ask questions of the data available to you and build a 360-degree view of your customers and prospects.

  • What demographics are your products likely to appeal to?
  • What demographics have constituted your historical customer base?
  • What channels are prospects coming to you from?
  • What offers resonate the most with prospects?
  • Do paid ads drive the majority of your traffic?
  • What pages and content on your website produce the highest retention rates and session length?
  • Where on social media do current customers and prospects seem to engage with you the most?

Unifying all of this customer data will give you a clear picture of customer and prospect search and purchase behavior. This data is invaluable, because it lets you shift from a reactive approach to a proactive, prescriptive one. The prospects you are trying to reach are on a journey, but the destination is open-ended. Your historical data on the journeys your customers have taken in the past can inform your strategy to connect with prospects at the optimal point in their current journeys.

Nobody wants to lose customers, but even data on defections can provide immense benefit to a company. You can use data from surveys, web browsing, social media, sales, ads and more to identify the pain points that have caused prospects to abandon your company or your products during the customer journey.

Once you understand obstacles facing customers and prospects, you can refine your customer engagement process (provide richer content, more frequent communication with clearer CTAs, more responsive customer service) to make your company more appealing.

Prescriptive Analytics to Guide the Customer Journey

As your company seeks to position itself as the trustworthy guide customers are seeking during their purchase journeys, you likely have a lot of data available to help inform your strategy. The problem doesn’t lie in capturing customer journey data; it lies in activating that data.

It can be tough to effectively utilize all the data your company captures. Big data, like we’re talking about here, is complex; there’s a huge amount of it, and it comes in all shapes and sizes. How can you best manage that data, drawing insights from it and using it to build a customer journey engagement plan?

That’s where Zirobi comes in.

With machine learning and data analytics tools, we can help you understand how to best engage prospects at all stages of the customer journey. By utilizing prescriptive analytics, you can move from an understanding of what prospects want to know to knowing how to draw them into your sales funnel. And when your prospects reach the end of the customer journey, our attribution modeling will show you how you can improve even further in your customer interactions and drive even higher ROI on your marketing dollars.

Using data to impact the customer journey is the future, and the data analysts and marketing strategists at Zirobi will make sure you don’t get left behind.

Let’s talk today.

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A full-funnel, fun-loving marketer, AnnMarie uses data findings to craft marketing strategies for every stage of the customer journey. She’s seasoned in customer segmentation, digital media buying, lead generation and content strategy development, using her knowledge to help ensure a fantastic customer experience for all.

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