Retail leans toward being reactive by nature. As you know all too well, a bad weekend sales report can make for a very bad Monday, often triggering a cascade of reactive measures requiring all hands-on deck. As a retail CRM leader, it’s easy to get caught up in the ensuing chaos.
What follows is a list of CRM activities that you can take to ensure you’re being proactive where it counts. Think of it as the checklist for your annual CRM tune-up.
What are the activities in CRM?
Since every organization differs as to where they are on their CRM journey, and CRM activities also relate to customer life cycle, the activities you focus on can vary from company to company. But we’ll start by highlighting a few basics that should form the CRM foundation for everyone, and then we’ll move on to more advanced activities in CRM. Here’s quick overview of what we’ll cover:
- Perform a data audit
- Perform a policy audit
- Update your customer segments
- Augment your data
- Combine segmentation with primary research
- Recognize best customers
- Review and update your customer journeys
- Optimize your loyalty program
- Engage your customers with content
- Investigate CRM re-targeting
- Move geo-location/beaconing into action
- Leverage artificial intelligence
- Consider clienteling
- Do a deeper dive on your unstructured data text analytics
Examples of Basic CRM Activities
Since every organization differs as to where they are on their CRM journey, we’ll start with a few basics before moving on to more advanced activities in CRM.
Stay proactive about data integrity and accessibility.
It goes without saying that the best CRM strategy in the world cannot make up for poor data practices. And, in this area, the devil is truly in the details. Your cache of customer data is a business asset that requires constant upkeep.
What does this mean for a CRM leader who is not hands-on with data hygiene? You can still be invaluable by thinking about customer data from strategic and analytic standpoints.
On the analytics side, at about two-thirds of organizations, analysts spend most of their time on data-related tasks versus analytic ones. This often means your analysts spend endless hours cleaning and preparing data so that it can provide a usable dataset for analysis. Bad or incomplete records are a frequent culprit.
On the strategic side, a University of Texas study provides detailed analysis on the strategic value of improving data effectiveness and is a great source of metrics if you are trying to build a business case. The study showed that when both data accessibility and intelligence are increased by 10 percent, revenue generated through new customers increases by 0.7 percent. That may sound like a small figure, but when applied to the median organization in the study’s data sample, it increased annual new customer revenue by $14.7 million.
Perform a data audit. With the end-objective of ensuring that you’re capturing the cleanest customer data possible, consider performing a data audit, mapping out the entry points for data about your customer: POS, app, eComm, customer service, etc. Make sure, for instance, there are systems in place that verify email addresses in real time, as they’re initially entered, providing error messages when the @ is missing or a common domain name appears to be misspelled.
As part of the data audit, perform a data penetration study. This looks at each field in your master customer record layout and provides a percentage value of how many records in that field are populated with data. According to a study by Experian, 91 percent of companies complain of common data errors: incomplete or missing data, outdated information and inaccurate data. Most believe this wastes an average of 12 percent of revenue. One way to judge if you have a problem with data quality is to compare yourself to retail industry benchmarks. For instance, consider these benchmarks for email data from Linchpin SEO:
- Open Rate: 21.33%
- CTR: 2.63%
- Unsubscribe Rate: 0.28%
- Bounce Rate: 0.36%
If you’re tracking below industry average on one or more benchmark, you have a problem you should dig into.
Quick tip: If you don’t already have an email preference center, get one. This allows your customers to designate how often they receive communications from you and to indicate their preferences for the types of communications they get from you. Many retailers have found that having a preference center has saved customer relationships and reduced unsubscribe rates.
Perform a policy audit. I know, I know. None of this is “sexy” — but it is an investment that will save you headaches, revenue loss and potential liability in the future. As part of this effort, review and ensure that the proper opt-ins are in place for all email and SMS data intake. The Direct Marketing Association is a great resource for the latest guidelines. It’s worthwhile to periodically review them to ensure you are in compliance as state and federal laws do change: DMA’s Marketing Permissions Guidance.
Take understanding your customers to the next level.
Most retail organizations understand the value of customer data in driving insights that can be used to drive strategy throughout the enterprise. Following are suggestions to help you take your understanding of your customers to the next level.
Update your customer segments. If you have not updated your customer segment clusters in four years or more, it’s probably time. After all, you use clustering algorithms to segment your customers into groups where they are similar to one another (and dissimilar to other clusters), and the point is to essentially let the “data speak.” If you have newly collected data, it could impact the resulting clusters.
For instance, you may find “app usage” is one of the defining characteristics for “younger and working” segments, but not a factor at all in “older and retired” customer clusters. Use of retail apps was far less widespread five years ago, so it wasn’t on the radar or in retail databases as a collected attribute. With the rate of change ever-increasing, make sure your customer segments change with the times.
Augment your data. In that same vein, if you haven’t augmented your own data with third-party data in a while, it may be time to consider updating that, as well. Obviously, demographics change and evolve over time and if not kept updated, they become less and less useful. In addition, the breadth of third-party data available can provide insights into customer behavior and intent. Third-party data can augment and fill gaps around what you know about your customers.
Order the combo: Combine segmentation with primary research. A very useful approach to better understand customer needs and motivations is to conduct research and view the results by customer segment. This is easy to do on the back-end with customer survey response data.
On the front end, you can organize segment-homogeneous focus groups. Since group dynamics can make or break a good focus group session, having customers who are members of the same segment in the same room can make a huge difference in getting everyone to open up and allow you to drill down on understanding their needs and motivations.
Recognize best customers. What have you done for your VERY best customers lately? Say, your top 100 or 1,000? Do you know who they are? It can be quite illuminating to look at the data at a customer level: purchase history, demographics, channel history, etc. Some may be buying from you for a professional purpose — for example, a representative from a corporate entity buying tennis shoes for all the kids on the inner city baseball team they sponsor. Others may be making frequent and large purchases for personal reasons. One grocery chain had a customer that spent almost $50,000 a year with them. This customer was feeding a large family of 13 (which included 11 growing boys). Oiy!
Regardless of the reason, these customers deserve some extra recognition. One home décor and furnishings retailer determined that they had just over 1,000 customers who spent more than $22,000 a year at their store. These were not decorating professionals. They were simply consumers who loved to change the look of their homes with the seasons. The retailer sent these customers a thank you letter from the CEO, inviting them into the store to receive a special gift. When the customers came into a store, associates were instructed to notify the store manager, who personally thanked the customer while presenting them with a gift.
One high-end luxury designer retailer went all out and gave each of their very top customers a special edition designer jacket. The retailer felt that the $500 cost of the jacket was well worth the investment with this group of customers who spent over $100,000 a year at their stores.
So, ask the question: Who are our very best customers and what can we do for them?
Further reading: Defining “best” customers can be a matter for debate. Many organizations find it useful to develop a customized value score that takes into account a myriad of variables in addition to how much a customer spends. To learn more, see Customer Value Marketing: Have you scored your customers today?
Examples of Intermediate CRM Activities
Once you have the basics handled, check these intermediate CRM activities off your list.
Review and update your customer journeys. Customer journeys should be updated frequently. All too often, though, they sit on shelves or on the hard drives in a CRM leader’s office. If you have not done so in a while, dust them off and review — omitting ones that have become obsolete, tweaking and pruning ones still in play, and adding new ones as needed.
With the rise of digital native generations, you may find you need to completely re-vamp your journeys. Ask yourself: Are there new channels that can be added into your matrix?
Have you added a chatbot to your website, for instance, but none of your journeys reflect this as a possible touchpoint? Have you suddenly noticed an up-surge in activity coming from a hitherto unknown social media channel?
Every social and/or technological trend has the potential to require an overhaul of the customer journey. Just think of the emergence of connected technologies over the past 12 months — wearables, Internet of Things, beacons, and so on!
Optimize your loyalty program. How many times have you looked at a list of the retailer loyalty benefits that included “birthday surprise,” “special members-only sale events” and “advance notice of sales and promotions.” Yawn. And if we’re yawning, you can bet customers are tuning out.
Many retail programs have become static monoliths that neither truly support the brand or excite our customers. Declining enrollment and reward redemption trends are big indicators your customers have better things to do.
Statistical benefits optimization offers one solution. It can help unearth untapped potential benefits that will have your customers singing with joy — and shopping. Statistical benefits optimization uses both multivariate and TURF analysis to quantify the reach and desirability of existing and potential program benefits. The result is the optimal mix of benefits for each of your key audiences, along with forecasted cost and predicted revenue impact for each benefit. (It also takes into account the aspirational impact for non-members and lower tiers.)
Engage your customers with content. Content continues to be king, but in the hustle of the retail environment, it can get overlooked or undervalued. Some brands are reporting that their content marketing initiatives are four times more effective than their traditional marketing campaigns, so it may be worth your consideration in your environment. The trick is finding a content niche you can own that builds your brand. Here are examples of retailers who do a great job owning it:
Examples of Advanced CRM Activities
If you consider yourself an advanced CRM retailer, you are in the enviable position of likely having the essentials in place, leaving you room and head space to try something new. Below are CRM activity ideas to get your creative and strategic juices flowing.
Investigate CRM re-targeting. Traditional re-targeting serves online ads to previous website visitors. But a CRM re-targeting strategy utilizes your offline customer data (i.e., loyalty member emails), “onboards” that data to match it with an online customer identity (i.e., known cookies associated with that individual) and serves up banner ads to those people.
If you utilize a deterministic onboarding methodology, you’re assured that your ads will reach the right people. With a probabilistic approach, you can only say that you’re probably reaching the right people — as well others with similar characteristics. The right onboarding approach depends on the application and how crucial it is to reach a particular individual.
CRM re-targeting can be extremely helpful — for instance, as a support to your new customer bounce-back strategy, promoting private label cardholder activation, promoting a special event to your VIPs, etc. It can also be employed to help you develop an opt-in program to purchased third-party email lists, as these emails can be onboarded and the consumers targeted with a banner ad that provides a strong value proposition to opt-in and provide their email. The possibilities are endless, and if CRM re-targeting isn’t yet on your radar, it should be.
Move geo-location/beaconing off your radar and into action. In late 2017, Target announced that it was rolling out beacon technology in all of its stores after testing it for two years. That could be the signal all retailers need that it’s time to move this tactic out of “radar mode” and into an action plan. The promise is great: supplying data on customers’ movements around and in stores, identifying repeat shoppers and linking them to their transactional data and, of course using the technology to broadcast geo-located messages.
Leverage artificial intelligence. AI is firmly becoming established in mainstream marketing, with Salesforce designating Einstein as its AI engine in 2017. Fashion footwear brand Aldo is currently using Salesforce Einstein to integrate multiple data sources and utilize data to create predictive customer journeys. In other words, helping to predict where a potential customer is in the sales cycle and which communication channels they will respond to. These one-to-one journeys are scaled across multiple channels, including email, mobile, social, digital advertising, online and in-store.
As with all technologies that hold a great deal of promise, AI marketing runs the risk of becoming the next “new, shiny object.” So, with many retailers tightening their belts, it’s hyper-critical to build a strategic vision before investing in a technology like AI. Strategically and properly employed, using artificial intelligence in marketing initiatives can be a boon to CRM marketers, providing an important tool to build customer engagement and loyalty.
Consider clienteling. What’s new is old and old is new. The oft-cited “shopkeeper of old” would maintain a list of his customers, their purchases and preferences so he could better cater to them. It was just good retailing.
Today, high-touch retailers are enabling store managers and associates access to see their customers’ purchase history and preferences as part of an effort to better serve and “manage” those customers with a personal touch. In concept, it is automating the “books of business” that associates of old would personally maintain on their customers (and often take with them if they left). Nordstrom and Prada are both testing this centralized clienteling concept.
Do a deeper dive on your unstructured data text analytics. Data collected from certain customer interactions are considered “unstructured” — meaning it’s not in a form that is easy for machines to understand. This typically includes customer reviews, surveys and comment cards, call center transcripts, live chat and social media interactions.
Many companies already use sentiment tracking solutions to help determine customer sentiment levels expressed via social media. The next phase is to combine sentiment analysis with “natural language processing” (NLP) to help you understand the cause of that sentiment level. (Note: NLP is the underlying technology supporting customer service chatbots.)
When an NLP engine reviews a call center transcript, for instance, it breaks the content down to its minimal components, such as think words, linguistic patterns and punctuation. It then builds these components back up into a structure to interpret the customer’s basic intent, potentially providing powerful insights to retail marketing leaders. Additionally, the process allows unstructured data to be stored in the same format as structured data, giving marketers a more complete picture of customer behavior and intent than ever before.
Roadmap Your CRM Campaign Activities
Let’s be real. The fast-paced nature of retail means our reactive tendencies aren’t likely to change anytime soon. But that doesn’t mean you can’t take proactive measures here and there. When you slip into one of those rare moments of peace, spend a sliver of it taking stock of your CRM activities. How many boxes can you check off our list? Are the basics in place? Are you ready to test out something new from the advanced pool?
Set a roadmap in place for where you want to take your CRM activities. It can be your rock when the inevitable turmoil ensues. And it can go a long way toward helping you reach your long-term, strategic customer retention goals.
As part of our retail marketing services, CCG’s CRM and loyalty marketing experts have helped retailers across North America develop, review and refresh their CRM activities and improve customer relationships. Let’s see what we can do for you. Email us or call 800.525.0313 today for a free consultation.
Sandra Gudat is president & CEO of Customer Communications Group (CCG), a full-service customer relationship marketing (CRM) agency that helps Fortune 2000 retailers and financial institutions improve their bottom line by improving their customer relationships, loyalty and retention.