How to find a customer conversation in Engage
Respond retrieves new messages from your customers, and organizes them into a simple workflow. Sometimes you need to go back and find a particular customer’s conversation history, or look for an author amongst a sea of assigned or closed messages. Let's take a look at how we can do this in Respond.
Finding a conversation, where to look
There are a few factors to consider when searching for a particular author:
- Which channel did they reach out to you on?
- What type of message did they send (direct message/comment/public post)?
- What’s their name?
- How long ago did they contact you?
The more of these questions you’re able to answer, the easier it will be to find your customer. Each can be answered by including Tier 3 filters to your current Deep Dive, in addition to your existing Tier 1 and 2 filters.
Running a search
During an average day in Lexer Engage, you’re probably running a set of default filters, or using a Saved Dive set up specifically for your team. The results returned from this search will have included messages from the person you’re looking for.
With this in mind, a typical setup will have:
- Your Tier 1 filters looking for content sent to your company/brand’s social pages
- Your Tier 2 filters retrieving all new messages, and potentially those in progress by other members of your team.
We know the message exists somewhere in the results obtained by your Tier 1 filters, so we’re just going to change your Tier 2 to look for messages in a “closed” state.
Most Engage setups will have a Tier 2 filter called All messages, All objects, or All status. If you’re having trouble finding the right Tier 2 filter, reach out to your Customer Success manager, or contact Lexer Support.
Open your date range
Next, we’re going to extend the date range. Chances are, the person you’re looking for has contacted you outside of the time period you're currently searching. We recommend selecting Last 30 days from the date filter in your Deep Dive.
Using the Author Name filter
This filter is your best friend if you’re looking for a particular author. The key is knowing how to search for their name, as this will vary, depending on the source through which they contacted you. Searching for authors is not case sensitive.
For each social network, this is how you’ll search for an author:
How to search
You can search for the full name in quotes if you know the exact name of the customer, resulting in a narrow query.
You can just provide either the first or last name as a broader query.
You can search for the username - drop the @ from your search.
You can also search for customers using the display name on Twitter.
You must provide the entire username for Instagram authors.
You can search for emails using their email address.
You can also search for emails using their first or last name.
Look for key words
Can’t remember the name of your customer? But you do remember something specific they said to you… that’s where the Matching Terms filter comes in.
Perhaps they mentioned their nickname, an unusual place name, or used an uncommon word or phrase. These are the things to look for.
For example, if your customer said “Howdy, Suze here! Do you deliver to Yackandandah?”
The memorable words in this might be “Howdy”, “Suze”, and “Yackandandah” - so depending on how much of the conversation you remember, you might conduct a search that looks like this
Tips and tricks
It’s not always necessary to strip your search back to the basics. If you have an open conversation with your customer, and want to see historical engagements, you have the following options:
Instantly add the author to your Deep Dive
If you have an open message with the customer, simply click on the author’s name on the message to add this to your Deep Dive. Ensure there’s nothing in your search that might conflict with your objective, like a “Closed messages” filter, for example, and run your search again.
View the Context and History panels
To the right of the message you’re working on is a panel with 3 options:
Here we’re going to focus on the History tab, but you can read more about the other two options here.
The History tab will show you a linear calendar of a customer’s interactions with all of your integrated accounts. It can be used to understand previous conversations with your brand, whilst providing you with the tools to identify older messages that may be amongst your closed messages. You can do this by selecting any of the messages in the engagement history
Export conversations from Activity
In Activity, there’s a whole wealth of information you can retrieve from the conversation data.
You can export from all charts and tables in Activity. In particular, the Responses table in SLA has super helpful data that you can find, filter, sort, and analyze, to get a better understanding of your interactions. Not only does this allow you to hone in on individual customers, but you can use this to see trends in things like query types through Classifications used, volume peaks and troughs, agent SLAs, and much more.
Finding your own content
In the same way you might wish to track down something a customer sent to you, you may also like to know what the reply was. This could be a message sent by yourself, or another member of your team - the search is the same.
Using methods set out in this article, you can search for your own content, but knowing the name of the author (that’s you!) gives you a head start.
Generally, your brand’s Tier 1 filters will exclude your own content, so we’d start by removing them, and instead, look for all social content. Your configuration may already have a Tier 1 filter called “All Social”, or something similar.
You’re then going to want to change your Tier 2 filter to look for everything pulled in by your Tier 1, so change this to ask for that. You may have a filter called “All messages”, or similar.
Add an Author Name filter to your Deep Dive, and enter your brand’s Page name/Twitter handle etc.
Now you’ll be presented with everything published by your Page. This is likely going to be a lot of content to sift through, so you can narrow down your search by editing the date range, and add a Source Name filter if you know what channel this was published on.
If you’d like to know more, reach out!
Contact us on live chat in the Lexer platform, or email us at email@example.com for further assistance.