The ROI of World-Class Social Care
By Edwin Margulies
One of the biggest questions practitioners of customer service ask regarding social engagement is "What about the ROI?" If you are embarking on a new social engagement for customer care initiative, you are probably thinking of all the ways you can improve efficiency and retain customers. Here are some guidelines that should get you started.
What are the ROI Hot Spots?
There are several hot spots I recommend you consider. They are: a) agent efficiency; b) customer retention; and c) up-sell / cross-sell. If you are doing sales campaigning and brand management there are other hotspots too but for this article we will concentrate on the ones most associated with customer care.
You may wonder just what makes agents more efficient in a social care context. There are three areas of concentration that pop up. They are:
- Spam Elimination
- Author and Post Attribute Search
- Agent Assistance Tools
Spam Elimination. Social care agents using first-generation social listening and engagement tools spend most of their time slogging through spam. Some companies report that as much as 80% of agents' time is spent eyeballing non-relevant posts. (Any post that an agent cannot take action on is pretty much spam).
Spam can be eliminated by using sophisticated filtering techniques and employing NLP (Natural Language Processing) technology. The result is awesome if done right. In essence, you can recapture as much as 50% or more of your agents' time depending on how tightly you tune the NLP engine. You can reduce the number of people you need doing social engagement and have them work on other urgent service issues, or you can handle more interactions with the same number of people which leads to better retention and upwell opportunities. Either way you cut it, saving as much as 50% of your agents' time can have a profound effect on your operation.
Author and Post Attribute Search. Agents spend a lot of time "hunting and pecking" for information on authors and other attributes of posts such as conversation topics. If you are managing multiple social sources for each author, it is tedious to jump around to look for post themes from that author. Providing a tool that allows for a programmatic author search can shave several minutes off of each transaction. This important because you don't want agents just "winging it" without doing any research on what other agents may have said to a certain customer.
By using a searchable timeline, agents can drill-down by conversation thread and author so they can identify related issues and research colleagues' responses easily. You will have to use a stopwatch to see how long a manual search takes to do this same function. If you break it down by transaction you can get a pretty good handle on how much time you will be saving per agent per day.
Agent assistance tools. Most agent efficiency gains are based on the idea of reducing "talk time" and keystrokes for agents. With the proper agent assistance tools, you can do this easily. For example, the ability for agents to do semi-automatic response text fills is sublime. Imagine being able to use a simple drop-down list to chose from canned answers - even including URLs to knowledge base articles.
The same could be said for Next Best Action scripts. These type of agent assistance tools can easily save ten to fifteen seconds on each transaction.
Another hot spot deals with how many more customers you can "talk off the ledge" if every agent has more time to spend with real customers versus wasting time on non-relevant or lower-priority posts. That is to say that the ROI from using Spam Elimination tools could be considered a customer retention tool versus an agent efficiency tool. The way to figure this is simple. First, calculate the lifetime value or annual contract value of a customer. Second, calculate the cost of new customer acquisition. Maybe the first is $2,000 and the second is $150. That's a total of $2,150 saved each time you are able to retain a customer who otherwise would have left for a competitor.
From an ROI calculation perspective, you'll need to estimate how many customers, in an agent's queue of social posts are ripe for churn. Consider now what is this number would be both with and without advanced filtering. That is to say that modern platforms can put you in a position where most of your agents are only seeing posts from angry customers that sincerely need help. Now if you don't have to see non-relevant posts, you can outreach to four or five times the customers in the same hour as before.
Also consider the fact that social media is used to communicate sentiment and publish likes and dislikes of vendors and their products and services. If you simply ignore an angry post in which your brand is maligned, not only do you miss the opportunity to reach out and do something about it for that customer, but you also have viral exposure owing to the fact that that post may have poisoned other people against your brand. This compounding effect would be hard to calculate from an ROI perspective, but it's something to ponder.
Up-Sell and Cross-Sell Opportunities
I mentioned how we would be concentrating here mostly on customer service ROI, but it is plain that inbound requests for service can easily be converted to up-sell opportunities. This can be done by pushing coupons or offers to a customer at the end of each transaction.
For example, you can say: "I hope I've been helpful to you today. Here is a URL for a coupon for the XYZ product: bit.ly/8iu7a." You can tag each end-of-transaction post with such an upgrade or cross-sell URL. Any business you get from these offers is fair game for an ROI calculation. The question is: "How many more of these offers can you make if you are able to use agent assistance scripts and pre-formed offer URLs that semi- or automatically populate the response window for your agents' posts?"
Let's say that with agent assistance scripts that you adapt for up-sell or cross-sell, you are able to send out 50 more offers a day directly to qualified customers. This could be based on a combination of spam elimination and agent scripting uplift. In other words, you could calculate the revenue from the up-sell and cross-sell and discount the actual agent efficiency numbers so you are not double counting. Clearly the way to calculate this will depend on the ROI style of your company and your peers. Getting buy-in on the assumptions up front is a useful exercise.
Whether it's agent efficiency, customer retention; or up-sell / cross-sell opportunities, you can easily build an ROI business case for advanced social engagement for customer care. Advanced filtering, spam elimination and agent assistance tools all figure in to these calculations. To get started, calculate loaded hourly cost, retention dollars, and up-sell projections and use them as baseline assumptions. Add the hourly activity on top of these and use a factor based on time saved for each agent in each activity. You can base your ROI on efficiency itself, or take a different approach that is more revenue-based.