Growth looks different for each company, but there are generally a few core tenets companies must adhere to: hire the right people, provide superior customer service, and engage in the right form of targeted marketing.
Those key elements will help your company acquire the customers you want. But once you have those customers, how do you get more like them?
By analyzing your most successful customer interactions and understanding customers' goals, you can better inform your marketing efforts to replicate your best and favorite customers.
So how is that done? Let's break it down into a few key steps.
1. Define your best audience, and find where they hang out
To replicate your best customers, you first need to define who they are at their core. That can be done by tapping into data you likely already have on them.
Look at the attributes of your current customers:
- What industries do they work in?
- What is their role in their organization?
- What pain points does your company or product help them address?
- What do their engagement and attitudinal data (feelings, motivations, and opinions toward a product, brand, or customer experience) tell you?
- Which ones are bringing in the most revenue for you?
After you've collected the data, look for common patterns and themes.
Those patterns and themes ultimately provide a data-driven picture of who your best customer is and, therefore, who your lookalike best customers are. And to reach those best customer prospects, you will need specific messaging at the right place and at the right time.
2. Use AI for data-crunching and creating predictive audience models
Although data can be pulled together manually, a lot of companies aren't sure how to scale it. An automated approach can help you continually build digital intelligence regarding your customers.
Because artificial intelligence can create simulation models and customize buying processes through suggestions and predictions stemming from machine-learning technology, many companies now use AI to determine the courses of action they should take with their target audiences. For example, AI can suggest products based on earlier purchases, pageviews, and inquiries.
The first thought many have in regard to using AI is, "I don't have the data to do this," when, in reality, they do. Though the quality of your data might be questionable, there are ways to mitigate that concern.
For example, a lot of manufacturers have siloed data in their organization; it's just a matter of being able to connect and crunch the data to determine who your best customers are—and then assess the quality and quantity of the output.
Ultimately, cloning your next best customers starts with such data-crunching and eventually moves on to creating audience models. Those models can take several forms; ideally, though, you'll use a predictive audience type model. Those data-driven models work to identify your next best customers through leading (predictive) indicators, such as these:
- Product affinities: What items customers purchase together while shopping
- Customer lifetime value: The total worth to a business of a customer over the entire period of their relationship
- Promotion engagement: Discounts, rebates, etc.
When building these predictive audience models, you will still rely on typical data points—channel and website engagement, demographics, and psychographic information as well.
The AI tool you use will help you to crunch the data much more quickly using machine-learning, and automatically send those audience suggestions to your other platforms, including for marketing (marketing automation, Google ads, social platforms, etc.) but also other key areas of your business, such as your sales CRM and customer service tool.
Marketers can use the predictive audiences to not only find net-new customers but also mine your current database for lookalike customers and provide them with meaningful product recommendations.
Even at the engagement level, marketers can look at predictive audiences to know who might unsubscribe from their ad or email channels and adjust their channel communications to avoid unsubscribes from those customers before it happens, which will save valuable touchpoints and dollars in the meantime.
Using tools like Salesforce Einstein, which is a comprehensive AI for CRM, is very helpful here because it automatically helps you crunch your data at scale (faster than our human brains and hands can process data!) and target these kinds of customer-acquisition and current-customer growth opportunities.
3. Arm your internal team with the data to 'digitally hunt' clones
Once the data is gathered and the picture of your ideal customers is more complete, your internal teams—those who have the most customer-facing roles, usually Marketing, Sales, and Service—can use that information for their campaigns or customer touchpoints to not only find and target the next wave of best customers but also deepen their share of wallet and delight your current customer base.
You might find that your next best customers are already in your own backyard!
Let's use the example of a company that makes and sells heavy-duty truck and trailer parts. It wants to find businesses that buy trucking parts online so that its marketers or salespeople can follow up with a personalized email. If the company has an existing database of 3,000 contacts, it's unrealistic for the salespeople to go through every contact, harvesting and cross-examining data points to make up models. Instead, the data they've collected can be fed into an AI tool that will help them choose the contacts who match up to their ideal target audience, ultimately narrowing down the list. By doing so and by subsequently creating a more targeted segment, you ensure your messaging will resonate more since it's designed for that specific audience—versus the "batch and blast" method that can lead to disengagement with your channels and your brand.
As privacy laws and regulations continue to become stricter, affecting how companies are able to track and use data, beware of purchasing and using third-party lists. Companies often purchase such lists with the hope of having a quick surge of contacts in their database that are "ideal" customers. However, those lists can quickly pose problems:
- Even though they are sold as "verified," it's not uncommon that those verified contacts are unreachable shortly after you purchase the list: people change jobs, update their names, and more.
- What's more important is that they have not opted in to receive communications from you, which puts you at risk of confronting CAN-SPAM and other regulatory issues.
- Moreover, people on such lists are likely to not only opt-out but also come away with a negative experience with your brand, which most definitely won't turn them into new (or repeat) customers.
Replicated customers = growth
With the right planning, data, and tools in place, you'll gain the complete picture of the best customers you're replicating. The result? Net-new acquisition of highly valuable customers and increased share of wallet within your own (existing customer) backyard.
More Resources on Customer Growth
Three Mad-Scientist Marketing Methods to Ignite Business Growth
How to Achieve Loyalty & Growth Through Customer Experience Excellence [Webinar]
Five Key Metrics You Need to Create a Customer-Centric Company
Enter your email address to keep reading ...
Demand Generation Articles
You may like these other MarketingProfs articles related to Demand Generation:
- Your SMB Needs a Full-Funnel Marketing Approach. Here's Where to Start.
- How to Build Marketing Automation Campaigns That Prompt Desired Behaviors From Your Leads
- How to Use the Awareness Stages to Nurture Leads From MQL to SQL
- Why It's Not Your Sales Team's Job to Nurture Leads
- How to Use Marketing Automation to Create Contextual Sales Conversations
- A 7-Step Inbound Marketing Lead Gen Strategy [Infographic]