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On-Target: Automated Targeted Communications

Today’s businesses know their customers better than ever before.

That customer knowledge has resulted in products that are now routinely customizable to a degree that thirty years ago would have been available only to the super-wealthy. The Model T Ford famously came in “any color … so long as it’s black”, whereas BMW’s Mini offers so many personalization options today that it has an entire website dedicated to it.

And it’s the same for customer communication. A TV ad shown to millions in the 1970s had to hit home with people of greatly different education levels, age brackets, expectations, and economic status. Now, though, data and technology mean that businesses can target their communication almost to the individual.

And it works. There’s a correlation between smaller market segment sizes and higher spend uplifts.

With the wealth of data companies have on customers today, segmentation can go beyond broad groups and even allow you as a customer communication manager to target individuals with relatively little effort.

But how?

Targeted Communication After the Sale

Marketing automation almost certainly forms a part of how your organization nurtures prospective customers. Someone downloads some content—perhaps an ebook—from your website and, although the content itself is free, they “pay” by sharing their email address. Your marketing automation system might then kick off a drip campaign promising more content or discounts. The system probably also tracks that person’s visits to your website and might even link up with your CRM to alert the sales team to give the potential customer a call.

Such automation is relatively simple: when a prospect behaves in a certain way, the marketing automation tool responds with predefined emails and, maybe, text messages to help push the person further down your sales funnel.

In fact, it’s not a million miles away from how most chatbots function today.

But what happens once someone converts? Maybe they receive a monthly customer newsletter and functional alerts—“your latest bill is ready”—but many companies leave it there.

Once someone becomes your customer, you can build a much richer picture of who they are and what their communication needs are likely to be.

Why Automate the Targeting of Your Customer Communication?

Automated targeting can benefit your organization in three main ways:

  • Reduce customer-initiated contact: well-targeted, automated communication can help anticipate customer needs and reduce the need for inbound queries.
  • Reduce churn: customers want to feel that companies understand them; automated targeting of customer communication lets you reach customers in the way that suits them, improving satisfaction.
  • Increase ARPU: marketing automation often stops when a prospect converts to becoming a customer; targeted automated customer communication helps upselling efforts.

At this stage you might be thinking, “So, the answer to all my problems is more email? Yeah, right.

And, of course, you’d be right to be skeptical if this was just about email. Instead, this is primarily about tuning your communication so that you reach each customer—or, more realistically, each customer type—in the way that resonates with them.

Parameters

What, then, are the parameters that you can tune to the needs of each customer? Broadly, they are:

  • channels
  • content and tone
  • timing
  • proposition

The instrumentation of your customer dashboard, apps, APIs, and other customer touchpoints will feed into your more traditional CRM and sales data to help you build a picture of the preferences of your customers.

Segmentation

You almost certainly already segment your customer base to some extent, but why? Surely it’d be better to target customers individually rather than to put them in broad groups. Well, of course, but in a world of largely manual data gathering and targeting it would be inefficient to create separate communications for each customer.

With automated targeting you can treat each customer as a segment of one.

Let’s take an example. Say your company distributes fresh fruit to retailers large and small. You’ll build a picture of each retailer from the ways in which they interact with your company.

Perhaps there’s a mom-and-pop corner store that prefers to phone in their weekly order on a Thursday afternoon, while a smaller chain in the same city uses your web-based ordering system every other day at 4pm. Your largest customer in that state, though, places daily orders directly from their ERP system using an integration with your API.

If you were to segment your communications by, say, revenue, then you might find that you end up having to put the mom-and-pop store in the same group as the small chain. But clearly those two types of store have different needs.

With automated targeting, you could instead create individual communications for each customer rather than groups of customers.

For example, at its simplest, you could send a text message to the same cellphone from which the small store’s proprietor calls in her orders. By sending that text message ten minutes before she usually makes her order, with details of that week’s offers tuned according to the season and that customer’s history, you’re using relatively simple data to maximise the effectiveness of your communication.

But that’s just the starting point. Every interaction that you have with a customer gives you potential insight into what communication methods are likely to be more effective but also the type of information they’ll prefer.

Targeting

Targeting doesn’t mean that segmentation goes away. Before you know a customer well enough, you’ll need to put them into broad customer segments. However, as they interact with your company you’ll learn enough to target them individually.

Now, this is where automated targeting starts to look a little like the way that chatbots work today.

Chatbots are not artificially intelligent. They don’t learn. At least, not yet. Instead, they follow rules set by their administrators.

Similarly, your targeting will be partly manual in that you’ll need to specify the parameters that matter to your customers and how that affects communication. For example, if your customer research tells you that 20 year olds in Ireland prefer WhatsApp over any other communication method, then you’ll need to prime your targeting to make sure that it starts off by using WhatsApp with 20 year olds in Ireland.

However, pretty soon you’ll be able to use off-the-shelf machine learning APIs to look at the response rates of individual customers. So, if one of your customers is a 20 year old in Dublin who happens to prefer SMS then in the future you might be able to use machine learning to adjust your targeting of that individual so that you contact them using SMS instead.

Targeting is Essential to Omnichannel

The promise of omnichannel communication is that you’ll have a single, unbroken conversation with customers wherever they are. The risk, though, is that your customers could feel overwhelmed.

Automated targeting—down to the level of the individual—will enable you to tune what you say, when you say it, and through which channel. So, while omnichannel will give you that ongoing conversation, it will also mean that when you contact customers that it’ll be with something they want to hear, at the time they want to hear it, and using the method that they prefer.

Even if some aspects aren’t quite ready yet, you can get started with automatic targeting today by instrumenting your customer touchpoints so they record the data you need in order to finely target your communication. And whether it’s voice, SMS, over-the-top messaging, or something else, you can use Nexmo’s APIs to begin implementing your omnichannel communication strategy.

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