“Focus on your best customers.” “Go after the big fish.” “Drive greater customer profitability.”
You have probably said some version of these statements to your team or have been given such mandates by your boss. And at first glance, they are all straightforward. little deeper reveals that words like “best”, “big”, and “profitability” can be interpreted in different ways.
Customer lifetime value (CLV) is a single metric that gets rid of the ambiguity. It incorporates sales revenue with all costs associated with each product or service sold. Customers who buy low-margin products will have a lower CLV than customers who buy high-margin products. Prospects who are likely to buy your products and keep purchasing them over time have a higher CLV than a “one and done” new customer. Obviously, you want to spend more time, effort, and marketing budget and selling to high-CLV customers and prospects.
CLV is a forward-looking metric based on historical data, customer/prospect firmographics, financial modeling, and predictive data sciences. It calculates the net present value of the future profitability of each individual customer and prospect. It may be complicated but the roadmap is simple: The more CLV the better.Calculating CLV is not an easy endeavor (or else you would have done it already). It requires a cross-functional team consisting of Finance, Sales, Marketing, IT, Operations, and Analytics professionals. These groups need to work together to:
With CLV, everyone in your company can agree on which products, customers, and prospects to focus on to improve corporate profitability.
B2B companies typically work with several Big Data sources – marketing automations, sales platform, billing system, and customer service to name a few. The sheer volume of data from these systems can be intimidating and taxing to an IT department. On top of that, business leaders are asking to have more and more new data sources (e.g., social media, natural language processing, operations performance) included in reporting and analysis.
This has precipitated in growing the popularity of creating a data lake for a company’s data. The data lake is basically one central location where data is placed from every system, platform, file, spreadsheet, audio file, and whatever else is deemed potentially valuable data. The good news is, all the data is in one place for people to access it. The bad news, it’s up to you to figure out which data to use, how to prepare it, and how to analyze it.
Don’t dive in headfirst.
There’s a lot of data in that lake. Make sure you are familiar with the different sources of data before you start using it – know the background on each source, which files can be joined to others, and how big the data is. Most importantly, have a clearly defined plan for how you are going to use the data in the lake and what business questions you want answered.
Use the buddy system.
If you are not an expert swimmer (in this case, a frequent user and analyzer of data), bring a buddy with you so you don’t get in over your head. Your buddy could be someone from IT, a Sales Ops reporting whiz, or someone from your analytics group. Bounce ideas off your buddy about the business questions you are trying to answer and how the data in the data lake can best be used.
Don’t go past the buoys.
Trying to do too much too soon may put you on a never-ending analysis path (and it will alienate your buddy). Start with some basic questions or challenges and use the data lake to address those. You will learn how to navigate the lake while also being viewed as a data-driven decision maker. Then move on to the more involved and challenging problems.
Know what’s in the water.
The data lake stores the data, but it doesn’t cleanse, transform, standardize, or join the data sources. It is up to you to learn what data you want to use. Have your buddy guide you to understand the data sources or direct you to the respective subject matter experts who know the details and pitfalls. You may find new data sources that you hadn’t considered and there may be data files that are too incomplete and inconsistent to even bother with.
Listen to the lifeguard.
Your IT director may not look the part, but he or she is the (figurative) person with the whistle telling you where you can swim and what the rules are. The data lake is not a complete free-for-all. There are data security rules, customer privacy considerations, storage space, and server access that IT still oversees. Follow the rules and stay on the good side of the lifeguard.
Businesses face many challenges today that impact traffic and same store sales. This includes pricing pressures, an aggressive competitive environment, a long- term decline in retail and slipping mall traffic, and an emerging generation of customers with different behavior than before. Amongst all of the challenges, businesses must have a deeper understanding of customers, their behaviors, demographics and attributes.
Marketing today must focus on current customers– who they are, how often they visit, and what they buy. In this environment, personalization is more important than ever. Businesses need to connect with their customers in a personal and relevant manner.
With the proliferation of data and online access, customers expect businesses to know them and everyone is fighting for their attention. Data is allowing many businesses to simplify, enhance and personalize the customer experience. Today, mobile apps track customers’ past and favorite orders for quick reorder and mobile pay makes it easy to get in and out of the store fast. POS systems show guest transaction history.
Websites make the right recommendations to customers. Some businesses are doing this well. However, many are not.
Our point of view is that businesses need to know their customers, show them that they know them and show them that they care. In an environment where customer loyalty can be fleeting, communicating relevant and personal information increases your bond with customers. Customer experience personalization is all about data first. Get the data right and you can shape the overall customer experience by applying data science and machine learning. Brands that personalize customer experiences by integrating advanced digital technologies and proprietary data are seeing revenues increase by 6 to 10 percent, which is 2 to 3 times faster than those that do not.
The following is our 4 step process to personalization for restaurant businesses that need to get on the journey of personalization.
Personalization starts with knowing who your customers are and what they deliver to your business. Integrate all your disparate customer data into a single place for analytics and action. Most businesses have many sources of customer data and it is often scattered throughout their organization; Certainly, point of sale transnational data that records all guest sales is highly valuable. In industries such as e-commerce and travel, the customer is identified. In restaurants and retail, this raw data is not connected to the customer. Other data sources such as online order information and guest e-club data and loyalty can be linked to transactions providing a starting point for knowing your customers.
Find Anonymous Customers
For businesses, there are external processes that can link a significant percentage of guests’ purchase data with point of sale data. This allows the companyto put a name and contact information to what would otherwise be unidentified purchase transactions. In many cases, this process can more than double the marketable customer base for a business.
Add intelligence to get 360 degree view of your customers
Start with a central repository of all guests data. Then append third party data to individual guests to get a view of not only their purchase behaviors but picture of who they are in life. Data appending allows businesses to fill in the gaps in customer data and add customer demographics (such as gender, age, income), lifestyle and interests (life driver segments, interests) and buying behaviors and attitudes (such as price sensitivity, technical aptitude).
Analyze and Summarize
With an organized and clean guest database, a business can now analyze and model guest data and determine the following:
Determine Your Strategy & Tactics
After you’ve defined some core opportunities, you can now determine your strategies and tactics to communicate with targeted guests. Determine relevant content and offers to guest segments and individuals based upon behaviors or demographics. Calculate the profitability of specific offers to understand the economic implications.
Drive Engagement with Relevant Offers
Knowing past behaviors and guest preferences, provide guests with meaningful and timely communications. For example, knowing your customers only shop at certain times of year and then offering products around that theme.
Integrate Your Plans
Integrate your customer communications with your overall plans to drive more business from customers in a manner that is relevant to them. Build out your calendar knowing your relevant holidays and high traffic periods. Leverage your vendors and to delight the customer.
This is where the art and science of marketing meet.
Set up Campaigns to Test List, Offers, Creative and Communication Channels.
Select customers and test various offers, creative and communications cadence. Dynamically personalize creative and deliver messages through channels that are most relevant to each guest. For example, an afternoon guest can receive a relevant email and mobile app messaging communication mid afternoon on a weekday versus a low tech guest receiving a direct mail postcard with a new special. Personalize your website experience based upon guest profile and behaviors. Reach guests in the channels where they are including mobile and social. In all cases, a clear message and a single call to action drives response.
Just to note, we are finding that direct mail is not a dead channel as some proclaim. While millennials are digital natives, 92% of them are influenced to make a purchase decision by direct mail as opposed to 78% of email.* Per the DMA 2015 report, direct mail response outperforms all other channels by 600%. Integrate online and offline communications. The goal is to engage customers to drive business and get a positive return on your marketing investment. Strategically invest more in high potential guests with an integrated campaign to drive greater business. DM costs are high but in the end it’s all about your ROI. You may spend more to get more.
Automate & Personalize Trigger Campaigns
Set up automated communications based upon lifestage or behaviors to drive customer engagement. These may include lapsed customer communications, daypart drivers, e-Club welcome communications, birthday offer, purchase thank you note and more. Add intelligence to these communications and personalize. Set them up once and automate this execution. Test and refresh campaigns as results are measurable.
Adhoc Marketing Opportunities
Launching new items will interest select customers. Market changes and promotions to targeted customers to drive repeat traffic with relevant communications. Respond to competitive actions or poor store performance with direct customer marketing to targeted guests in specific geographic areas.
Leverage your guest data and CRM tools to strategically invest in your guests with the right tools and dynamic execution.
Continual testing provides learning. For example, as a company is launched its campaign, they divided the campaign into three distinct groups based upon past behaviors. The targeted emails had 2x open rates and 5x purchase rates! Getting relevant with customers drives results.
The proof is in the results. Personalization gets the guest’s attention and drives engagement and sales.
Now is the time to drive more business through personalization. Know your customers, show them that you know them, and show them at you care. See what we can do for you.