Defining the Loyal Customer with Data

What is a “loyal” customer?

The loyal customer is a person who keeps coming back for more. This customer frequently browses, shops and supports your company. A loyal customer may consider other competitors, but often chooses your company when making purchases.

In other words, a loyal customer is your favorite kind of customer.

Why is defining the loyal customer with data helpful?

Companies should market to all types of consumers. However, marketing to loyal customers can give a business an edge when making sales.

The loyal customer also tends to be a more valuable customer. Selling to existing customers is about 50% easier than selling to new customers, according to Marketing Metrics. Loyal customers also churn a greater profit, according to Gartner Group. In 2012, the group found that 80% of a company’s future revenue comes from 20% of existing customers.

Brick-and-mortar loyalists

In small mom-and-pop shops or some brick-and-mortars, labeling the loyal customer can be easy. For example, I frequent my local brick-and-mortar Starbucks so often that the baristas have my order memorized. When I walk through the franchise’s doors, I am greeted with a friendly “Hello Savannah!” followed by, “Grande vanilla soy latte, right?”

Because I am face-to-face with my Starbucks baristas every day, my baristas can easily discern that I am a loyal Starbucks consumer. Because of this, they offer me a personal greeting and predict my order. This makes my experience more enjoyable and convenient.

But what about entities that aren’t privy to daily face-to-face interactions?

Digital loyalists

What is a digital loyalist?Determining loyal customers across digital entities can be a little more dynamic. With a significant portion of sales happening over the Internet, discerning which customers are loyal is important. However, it is not always as basic as face recognition.

Companies can analyze big data from their online sales to determine which customers are loyal. Integrating data and marketing can be more effective than remembering names and faces.

In the aforementioned Starbucks example, defining loyal customers can help a company personalize shopping experiences. This personalization is not limited to in-store interactions. Marketers can offer the same personalized greeting and predictive product suggestions digitally via email, SMS or website.

Marketers can use data several different ways to determine which customers are loyal. Special membership programs are the most obvious way to discern which customers are loyal. These CRM systems generally require customers to share personal information in exchange for special offers or discounts. Personal data is compiled to create a personalized customer profile. Companies can also use specific metrics to determine which customers are loyal. Metrics can track how many purchases a customer makes, and determine whether they are a one-time buyer or a loyal customer. Marketers can also use metrics to see which customers are opening, sharing, or unsubscribing to online content.

Adjusting personalization for one-time shoppers vs. loyalists

Distinguishing loyal customers can also help a company shape their marketing strategy. Businesses may change the way they market based off how likely a customer is to be a return customer.

Starbucks is one of those companies that adjusts its marketing strategy according to a customer’s loyalty. According to Business Insider, the coffee company offers most of its special offers to consumers who are not as likely to be return customers. Starbucks tries to attract these irregular buyers with these special offers, whereas it doesn’t feel the need to woo loyal customers because these loyalists do not require special offers to buy from Starbucks.

However, Starbucks does not ignore its loyal customers. Through its rewards program, Starbucks offers different types of offers for customers that are more loyal. Offers for Starbucks Gold members  – the most frequent Starbucks customers – encourage further purchases from a sect of consumers who are already frequent buyers. For example, customers at the Gold level have access to free in-store refills – a privilege reserved only for Gold members.

Through this unique type of personalization, Starbucks plays the marketing game based on the strength of its consumer relationships. If you’re intrigued about incorporating customer data in marketing, learn about clickstream data in an automated world.

3 Ways to Improve Mobile Personalization

Mobile Personalization

Mobile Personalization is one of the hottest new trends in marketing in 2014.  Mobile purchases make up about 20% of all eCommerce transactions and mobile sales are projected to increase from $139 Billion to $400 Billion in the next couple years alone.  It is apparent that mobile presence is growing rapidly, but the real question is “What is the best way to improve mobile presence and interaction?”

1. Push for increase in opt-ins: The first way to improve mobile presence is to push for an increase in opt-ins.  Opt-ins range from customers signing up via mobile devices with their personal information, allowing push notifications to their phone, and cross-promoting mobile offers through their desktop site.  By offering these opt-ins a company is able to gain more personal insight into customers that agree to this and personalize their mobile experience by including their name, deals and offers based on their geographic location, and more relevant product selection based on their previous transaction history.  In short, having these opted-in customers allows a company to associate more personally with the customer and create an opportunity for them to evolve from being a simple customer to an evangelist for your brand.

Mobile Personalization

2. Cross-channel Promotions: The second way to improve mobile presence is cross-channel promotions over mobile.  Within the mobile realm there are multiple ways to reach customers: SMS texts, Apps, social media, passbook, and mobile website.  There are various ways to get involved in this avenue of marketing and it can include text campaigns where potential customers can text a preset number for offers and rewards and thereby entering their phone numbers into a
database for a company.  Another method is to have an app developed for a brand.  This has the most flexibility as the app doesn’t have to serve any particular purpose other than collecting data.  It could be a game, a coupon generator, or any other form of entertainment.  As long as it gets downloaded then it is fulfilling its purpose and creating more personal contact with customers.

3. Geographic data: The final way to improve mobile presence is to tap into geographic data.  This can be done very simply just by having a feature in an app or website that utilizes the phone’s location services to determine
where a customer is and if there are any promotions that would benefit them at their current location.  One way to

Mobile Personalization

capitalize on location information is to send geographically defined text messages or emails to customers based on where they are.  If a customer in a shopping mall, for example, and then receive a text from a store offering a sale a clear call to action is created and it is more likely to be followed up with because of the proximity to the store.

As mobile presence increases and customers are more focused on their devices than ever before, marketers too must focus more on these devices.  The ability to capture customer data and create a more engaged experience for them is available but it’s a matter of acting on it and creating the avenues to acquire this data in the first place.  Once the mobile presence is improved, the results will be noticeable and by connecting with customers it can be expected that lifetime value and loyalty of those customers will be increased dramatically.

Using Big Data to Micro-Target: Integrating Big Data for 1:1 Marketing

personalization_social_media

One of the things I love about my job at Nectar is sharing with our customers how we deliver value to their business by enabling them to micro-target messages to their customers. Recently, while reading McKinsey Quarterly articles on big data, I saw a couple of statements from McKinsey directors that really resonated with me, because it addresses the core of Nectar’s value proposition.

1) From David Court: “…the key is to focus on the big decisions for which if you had better data, if you had better predictive ability, if you had a better ability to optimize, you’d make more money.”
2) From Tim McGuire: “Analytics will define the difference between the losers and winners going forward.”

I believe that if you make your customers happy, they will be loyal to you, and loyalty generally translates into greater revenue (and less cost) for your company. How do you make your customers happy? By knowing them. Know how they interact with you, know what they buy from you, know what they like about you, know who they are.  At an individual level.  Of course, this is easier said than done.  But with the right tools and data, it can be done.

When, where, what and how you communicate with your customer is one of those big decisions.  Using the data you already have from your customer and combining it with other big data–online behavior, social, CRM, mobile, etc.–enables you to predict what that customer would want to hear from you.  This predictive ability, in turn, allows you to optimize your relationship with that customer, which then helps you make more money.  (I use the singular “customer” because that’s what a robust Digital Management Platform enables you to do: communicate with each of your customers as an individual, yet do it at scale.)

Technology exists today to bring all of your available big data together to build a foundation from which to make your big decisions. A company like Nectar can help you bring all this data together to enable you to build 360 degree profiles of each of your customers.  But we don’t stop there; we then apply our proprietary algorithms to analyze your customer profiles to determine the most relevant communications to deliver to each customer–we call this hyper-personalization.  To complete the circle, we then help you distribute consistent hyper-personalized messages across every digital channel your customer uses.

We like our perch at the intersection of big data, analytics and hyper-personalization because when we bring each of these tools to bear for our customers, big decisions not only become easy but they also make you money.

Want to learn more?  Please email contact@nectarom.com for more information.

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