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Valued Contributor

does Lithium support User engagement enough?

Hi All,

 

I'd like to ask opinion about how much does Lithium support us in terms of user engagement?

and how easy? I created a below structure and want to know how much Lithium community itself support my structure or my wish list.

 

We found a bit difficult to do this - we can do filtering and get data of users based on filtering - but when we want to send private message to this filtered group - we cannot send. Plus, when we send private message (and cc: email of users) we got limit at 10,000 max per month. This is not practical to us.

 

Pls share your thoughs and suggest to me if you know the solution (that is easy) Thank you.

 

My wish:

 

manida-lithium-product-improvement.PNG

How we are doing:

 

manida-how-dtac-doing.PNG

It would be easier to be able to send private messages to filter group and cc: users’ email at one time click through the platform.

and the filter should be more varied

5 Replies 5
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Honored Contributor

@mojijoy

 

Good post. There would certainly be a lot of value from what you are proposing.

 

Unfortunately the platform doesn't currently offer an easy way to do what you have described. There would need to be a lot of manual reporting and data analysis, and then exporting to a CRM that could do the emailing for you. However @amanda_optly has done something similiar with a Salesforce integration to push data to Marketo - she might like to share her experiences to date. 

 

Here's a couple of relevant ideas exchange posts that you might like to add your vote and comments to:

 

Automatic emails or PMs following registration to guide new users

 

Build a Message Manager

 

Good luck,

 

Jason

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Commentator

Yes @mojijoy it will be good to have some easy way to reactivate dormant users with mass direct messaging instead of exporting the data and use an email system to send out the messages.  I have voted on the idea suggested on message manager. 

Tweet me at @bluefirefly2359
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This is near and dear to my heart, as I've been spending most of my days thinking about how as community professionals we're going to drive and show value of what we're doing every day to our organizations going forward. The good news is that we all have a lot of data about what is happening in our communities, but the platform lacks the necessary tools to go further.

 

In the context of this discussion, there are three components to think about:

 

  1. Tracking, storing, and (lightly) visualizing sets of data (LSI, Admin Metrics, User Reports)
  2. Blending, processing, and analyzing the data for insights (Excel tends to be the default tool)
  3. Ability to communicate with users to drive more engagement (third party e-mail tools like Marketo)

 

Lithium does #1 well and most organizations have solved #3 with tools like Marketo, leaving us with a gaping hole in the middle. It is easy enough to export a User Report or some .CSVs from LSI and use Excel to get a basic e-mail list, but do you really want to spend time doing all of these manual preparation and filtering operations every time you want to send an e-mail? I think we can do much better, so I spent a few minutes this morning creating a workflow in Alteryx to try and solve the immediate need in an easy, repeatable way.

 

 

Here are the details:

 

  1. Input - Export a User Report (Admin) and a Members report (LSI) for the area of the community that you're interested in per the original post. Input those files into the workflow.

  2. Cleanse, Join, and Prepare Data - the gray Data Prep container uses 7 tools to parse the User Report into a usable format by structuring and cleansing the data so that it is nice and clean.

    Because LSI reports do not contain personally identifiable information like e-mail addresses, we need to join both reports by username so to get the e-mail lists for Top Posters and Top Solution Authors. The Data Prep Select tool is simply dropping duplicate and unneeded data.

    Now that everything is well-structured and clean we can begin asking questions of the data.

  3. Process and Analyze Data - We're using series' of tools to filter, sort, select, and do some basic math (LSI gives you Topics Published and Replies Authored, but not Overall Posts...thus the formula tool). Imagine how much time you're saving by not having to manually do these operations in Excel every time you want to produce these lists. Set it up once and use it forever. Super powerful and super fast.

  4. Output Results - There are many different ways to output the data, but since we mentioned Marketo let's do that. When the workflow is run, it will do everything described above and output it directly into Marketo so that you're ready to fire off your e-mail. Pretty cool, right?

    With a normal amount of data in each report, the whole thing runs in a matter of seconds. You're done and onto the next thing.

 

Hopefully that is helpful to think about how you can start to approach these kinds of tasks in easier and faster ways. There is a ton of power in these kinds of tools that we can all benefit from.

 

If anyone is interested in trying this for themselves, click here for the workflow file and grab a free trial of Alteryx to run it.

 

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@BrianOblinger Thank you for your reply - it's really helpful.

 

So how do you measure the efficiency of the email/private mesg sent via community to users?

Ex. if you send email (or mesg via community) to Lurkers - how do you know that those users participate more from the email you sent.

 

(we tried to use Google Analytics)

 

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Marketo can give you the open rates and such for the email, so you'd have a good idea of the initial reaction to the mailing.

The next step would be to look at the data for a period of time before and after the email for the users you targeted to see if there was an increase in participation, engagement, etc. Advanced users could use some of the correlation tools in Alteryx to understand if any uplifts in the email group are actually related or just a general uplift across the community for the timeframe you're measuring.

Experiment > Measure > Analyze > Optimize > Repeat