0:01
Hello everyone and welcome to today's webinar hosted by info people. This webinar is sponsored by the California State Library as part of the 2019 2020 metrics Grant and our topic today is harnessing Library data Equity diversity and inclusion and ebook usage and to get us started. I'm going to go ahead and turn it over to one of our presenters Amanda Winchell.
0:26
Thank you. My name is Amanda Winchell and I am the North American sales manager for gam engage and Gail analytics and with me today is Lisa Lisa. Would you like to introduce yourself? Yeah. Hi everyone. My name is Lisa Nova Husky and I'm the marketing and analytics consultant here at Gail.
0:47
Lisa and thanks for joining us everybody first and foremost. I hope everybody is safe and healthy and just mentally and physically doing well. I know that this has been a very difficult - how long has it been now six weeks to months and it feels like a long time but when Lisa and I were preparing for this webinar probably two months ago.
1:09
We had a pretty, you know, pretty straightforward outline in mind and then then it seems like our world turned upside down and we really wanted to make sure that this webinar was relevant to the world that we are in today. So we wanted to the existing premise of you know, focusing on ebooks and focusing on the EDI EDI initiatives and libraries and really look at those through the lens of the pre and post covid environment. So so our plan for today as far as the agenda goes, we're really going to take a look at just a basic.
1:45
What Gail analytics is exactly and just a quick note about that for those of you that are not familiar with Dale analytics? Don't worry about that whatsoever. Because the main thing in this webinar today that I think you can get out of it is the fact that we're going to look at maybe data a little bit differently.
2:06
We're going to ask some different questions and I'm hoping what you get out of that is a new perspective of the data that you can analyze questions that you can ask and probably most Currently is the action that you can take on that. So don't let the fact that we are using a specific tool hang you up because there's a lot that you can get from that with or without the cool and then we'll go into examining the the data using the tool pre and post covid really looking at ebooks and EDI. Lisa is really going to go into some significant detail in that and then of course, we'll have a Q&A at the end.
2:43
So feel free to post Your questions via VIA chat, but we will try to get to as many as we can towards toward the end of the webinar. So really, let's dig into real briefly what Gail analytics is exactly. So just a brief introduction here. I'm just going to spend a couple of minutes on this and then I'm going to hand it over to Lisa.
3:06
So what is Gail analytics Gale analytics really allows you to take any kind of data that you In analyzing, it could be iOS data. It could be a book that it could be donor information. We've whatever kind of data it is that you have at the library. The tool allows you to upload that data into the tool. And then what happens is that that data is the married with the external information that we provide and that external information consists of the Experian Mosaic segmentation portal with get into in just a minute here. So which includes demographic data?
3:45
Lifestyle data will look at mapping will look at Geographic data. Of course US Census and American American Community survey data is Incorporated in that as well. So because the internal sources of data and we've got the external sources of data that come together in are married by one common denominator being the patron address.
4:06
Once that's processed in the cloud out will come a custom dashboard the dashboard might look a little bit differently depending upon what it is that That you want to analyze made again. Maybe it's ebooks. Maybe it is, you know physical collections whatever it might be but you'll be able to analyze that through a tableau dashboard one other piece of information here that's important to note is that your data never leaves your hand. So this always stays with you. It's processed in the cloud and then it comes right back to you so Gail nor nor does a third-party have access to any of that data as I had mentioned.
4:45
And just a minute ago a key a key component of Gail analytics is the experience segmentation portal that is available to you. And that's really unique Gail analytics. Yell, or I should say the experience segmentation system is truly the gold standard of segmentation systems that are out there. So come large companies like Coca-Cola or Walmart or Target, for example, I use this and they use this because they know that it works. They know that the segmentation system works.
5:15
It divides the US and 219 groups or 71 different types out there 71 different types based upon demographic characteristics. Lifestyle Behavior Etc. Now for those of you that might not be as familiar with segmentation. It's pretty simple. It's just really a way of dividing your data into groups. It could be income brackets or households with children or maybe you know a group of households.
5:43
For example, that might have a propensity to To the library regardless of what you're looking at grouping different people into these different segments really gives you greater Precision with your marketing because it really allows you to talk to each person in a way that's relevant to them.
6:02
And that's really the key with the segmentation system in a robust segmentation system that that because when we do the obvious the opposite which I think we're all you know, we've all done before is when you talk to the right person, but about The wrong thing we tend to drive them away and they might come back, you know for your second message. But if that doesn't appeal to them likely they're just going to unsubscribe from a newsletter or maybe just delete the email all together. So it's really important that we get our message. Right and that message is right for the right person and that's really what this Mosaic segmentation portal allows us to do. So what let's get into it for just a minute really how you can run a gale.
6:45
Report it's pretty straightforward. Basically, once you log into the admin tool and you have your data your first just going to add your library name address city state and zip pretty straightforward. And then the next part is where you're going to upload your your data. Now in this particular example that you see here on the screen. This is a patron file. So address last checkout date total number of checkouts.
7:15
Now if you want and to analyze ebooks, for example, then you're going to need to prepare some e-book data that would consist of genre information or format it cetera. But once you've uploaded your Patron file, then your next step is to really decide what kind of geography it is that you wanted to you. Wanted to analyze we've got a lot of different options there. Perhaps you want to teach at a school district. Maybe you want to take a look at your entire County, or maybe you have a custom GIS file, for example.
7:45
That's important for you to analyze regardless of where it is that you're looking to to analyze there is an option there. There should be an option there for you. And then finally once you've selected those your geography and truly the report or the data is processed and then out comes the the Tableau dashboard. I think there's one more one more slide there and this tableau.
8:15
Oh dashboard. Lisa's going to get into a lot more details on that. But basically this is going to give you your charts or graphs or mapping of all information that you had uploaded. And again that was really married with the external information that we had provided. So just a real quick note here for those individuals that would you know that needed perhaps login information for Gail analytics.
8:40
If you already subscribe feel free to reach out to me my information will be at the end or Thing with the segmentation portal as well. Feel free to reach out to me and I can certainly support do with that. And finally, I'm just going to turn it over to Lisa here so she can really dig into the nitty-gritty of those dashboards and help us to understand what data to look at and what questions to ask and what action we can take Lisa. Thanks Amanda. So as Amanda said I'm going to walk us through the sample analysis. I'll just start by giving a little bit of background and then we'll go through you know the wheel.
9:15
All of the steps of how to go about doing this analysis. So, you know last month many libraries across the country made the difficult decision to close their doors due to stay at home orders and social distancing apartments with the physical locations and materials not accessible to patrons many libraries have been you to shift from physical materials and resources to those available online.
9:39
It is both interesting and important for libraries to understand that shift in usage.
9:44
We can use the Gale analytics dashboard to examine you could be book comparing the user base before and after Library closures to understand what changed and if you use a base of this service grew additionally we can understand who the new Patron households are and we're within the service area the patron base expanded to the jail analytics dashboard and giving a demographic information.
10:19
You can rest afterwards. We can examine the usage of e-books pre and post closure by doing this we can understand the patron base to use ebooks while the library was still operating normally and we can then compare this group to the patron base using ebooks after the closure of physical library locations to understand how uses change if at all as a result of physical library locations clothing.
10:42
The first step in this process would be to obtain ebook transaction video. We would want the data to include transactions for both time period pre and post closure given the timing of Library closures. We can examine ebook transactions from the beginning of the year through the president giving us about two and a half months of ebook transactions pre closure and a few weeks to a month for the sake of Simplicity.
11:06
We will use for our webinar today, but if you want to compile a list of transactions, Form the process would be the same. There are two pieces of information. We require to use this data for this analysis the date of transaction and a patron identifier allowing us to match this data back to the patron information from the, Iowa.
11:27
here I have some overdrive data in its raw form at this is just sample data. It does not represent any library in particular. It is just sample data that we will use for our demonstration today. So you can see what the format looks like and how we would manipulate it. You'll see that we have many more Fields than the ones we need, but I'm going to start with the raw data to show you how to get this data into a usable format.
11:51
If you're on the data, you see we have the two Fields as talking about checked out which is highlighted in yellow. And if we scroll over to the right, you'll see we also have a user ID, which is a barcode. It could be some kind of a patron ID. It's whatever we'll use to match back to the iOS Bo.
12:08
So from here, there are two ways. You can proceed with this file. The first simpler path would be to take this list of transactions and divide it into to the period before the library closed and the period after this version of the analysis would give us a view of who is using Overdrive.
12:39
If you do this, what we would do is we would activate filters which is in the data tab on the ribbon of cops. If you click on filter, you'll see that little boxes of arrows show up in the right hand side of the headers. If we click on that we can start to filter for the dates that were interested in. So for example, if we were to do the pre closure period we would want to keep all transactions from January and February and from the first two weeks of March for example today. I'm going to use March 15th.
13:09
So in that case I would do.
13:21
I'd okay. And what that does is it filters out the transactions that were no longer interested in from here. What we would do is we would take the list of user IDs and call them X here and we would copy and paste them into a different tab that we can have this list of users. I've already done that here.
13:39
And the steps could be pretty much the same if we're going to do a post closure with so instead of the last two weeks of March we would take we would actually isolate those transactions and we would take away the transactions from January.
14:07
I hit okay here you'll see that the checked out dates now only include the last two weeks of March. And again, we would take the user IDs in this list and we would copy and paste them into another tab here. I have the post closure transaction.
14:22
By filtering the transactions and creating these lists. We now have a list of all barcodes for patrons who checked out overdrive materials during these two time period we will add additional information that we will need for deal analytics later. But for now, we have the full list of users. One thing to note.
14:37
It is perfectly fine that in each list will get duplicates of the patron barcodes if they had multiple transactions during each time period There is another way that we could get the list of patrons barcodes that had overdrive transactions during each time period if we wanted to get a little more complex, we could create a pivot table telling us not only the was using overdrive during each period but also how many checkouts they had during the two different time periods. We are observing. This is an added step that would provide a little more insight when visualizing overdrive users on the map as the size of the dock to use to visualize Patron households are based on checkout volume. I'm going to show you how to do that here.
15:18
Here first, what I would do is I would deactivate the filters by hitting the filter button up top. And then I would select the table using the upper left-hand Corner go to the insert section of the ribbon and then hit pivot table.
15:31
What is Thousands it asks you to select the table or range? So here at selects the full table, which is something we've collected before inserting the pivot if you hit okay, it'll bring us to a new tab that allows us to create a pivot table.
15:49
So here we have the pivot table with the field selector on the right. What I'm going to do is I'm going to select user ID and drag it into the road section on the bottom. And what that does is it gives us a unique list of all of the user IDs that show up in the transaction and then I'm going to take user ID and drag it into the value section over here. I'm going to click on the arrow on the right and click on value field settings and then switch the value of summarizations account.
16:15
And essentially what that does is it gives us a list of all the user IDs that show Up in the transactions and the number of times that user ID shows up in the data now, we're also going to want to filter for the checkout date so that we can understand the two different time period check out is the day the field that we were looking at previously. So I'm going to take that field and I'm going to drag it into the filters and similar to what we did previously you're just going to the selected the date you're interested in. So in this case, I'm going to hit select multiple items and to make a pre closure list. I'm going to go to the bottom of the list and deselect.
16:49
All of the dates at the end of March from March 15th until the 31st.
17:03
What you think here is a list of all the users who had transactions before the library closed your date you selected and the number of transactions they had now to do the same thing for check for post closure transactions, we would you know, select just the dates that we were interested in. So in this case, what we would want to do is we would do select all of the dates and then just select those from March 15th down to the 31st.
17:31
The Next Step would be to obtain a patron file from the iOS. There are two key pieces of information. We will need for this analysis the same patient identifiers. We find in the overdrive data, which can be a patron barcode or a patron ID and the patron household address for Gail analytics that we can look at. This is just a sample.
18:01
Says it does not represent. Any particular Library.
18:05
Next we would combine the two types of data that we have the household addresses for all patrons who have ebook transactions during this time period we can do this using Excel first. Let's take the list of patrons who had transactions before the library closed for the purposes of our demonstration today. I will use the pivot table. We just created giving us the list of patrons and the number of transactions they had during each period so switching back to the overdrive transactions.
18:30
Really, what you would do is you would go into the pivot table and just copy and paste the User IDs as well as the count.
18:39
I already created the list here.
18:44
Using the formula V lookup we can take the household address from the patron file and append them onto each individual Patron in the e-book transactions file. So first, I'm going to create a header here when it's call it a dress and then we're going to use the vlookup formula. So I would type equals vlookup. I would select the user ID that I want to be looked up. So in this case, it's LA to then I would go to the patron file. I would select the table for look up. So that's going to be the user ID and the address.
19:14
Put a comma and then I'm going to say two things take the second column in the table. And then I would type both to say give me the exact match.
19:23
What you see here, is that the formula looked at both tables and match them up together. So now we have the address that is associated with the first user ID in this list. You're not going to have to type this in Forever user. You have you can just perpetuate the formula like clicking double clicking on the little box that's on the bottom right hand corner. So you'll see that the address gets pulled in for every one of these users.
19:48
The final piece of information needed to use daily analytics is the last activity date in general. The last activity date can be used to isolate subsets of patrons based on their date of last activity our analysis today already accounts for the time period of usage. So we will simply put the library closer to March 15 for all of the patrons that the file has the correct structure and can be loaded into Google analytics. So you could last activity date up here.
20:17
And then we'll put March 15 and the same way. We did it for the formula. We can just perpetuate that for all users.
20:30
You would follow the same steps for the patrons who had transactions after the library closed in the interest of time. I've already done this for you soon our webinar, but know that you would follow the same exact steps for the second list of feature. Now that we have our data in a usable format. We are able to run the reports as Amanda already covered how to run a report earlier will skip this step one note. I'm running the dashboards. You would follow the same steps to run both the pre and post closure dashboard.
20:55
The only difference is 2 choosing the dataset that Gala For our webinar today, I run a dashboard for both time periods and have them ready for us to examine. Let's take a look at those dashboards now.
21:11
Okay, so we have the two dashboards one analyzing the patrons who checked out ebooks.
21:18
Using overdrive pre closure and a second and analyzing the patrons who checked out ebooks using overdrive after the library closed will first look at each dashboard individually to understand the demographics and The prominent Mosaic segments of each group of patrons, and then we can compare the two to understand how the patron base shifted and changed.
21:37
Let's start with the dashboard examining users of overdrive pre Library closure will start with the patron measures tab, which gives you some demographic information as well as identifies the most prominent Mosaic segments in the user base. We can look at these demographics here to get a better sense of who the library of serving with eBooks on overdrive as this dashboard represents usage of overdrive.
22:05
Let's take a look at it.
22:35
Made it household income bracket. And finally, we have the column titled number of Records which represents the percent of households in the full service area that fall into each estimated household income bracket. We can look at this data and interpret it by using the concept of proportionality while it is both interesting and important to know how many and what percent of patrons are in each estimated household income bracket. We can provide a little bit of extra contact by comparing it to the total number of households in the service area.
23:05
Yeah, we can look to the percent of households in the base that fall into each estimated household income bracket to understand the demographics of the area in general.
23:15
You would expect the We see here that the lower income brackets under $75,000 or underserved their households that are not utilized utilizing the service as heavily as we expect them to at around 75,000 dollars all the way up to $250,000 or more.
24:21
Fall into those income brackets if we look at the base column, we can see that only 38 percent of household in the full service area have an estimated household income in that range. That's a big difference. This is a really interesting Insight ebooks are heavily utilized service, but they require patrons have the technology to be able to access them because of this there's automatically a barrier to entry looking at the distribution of patrons here in this graphic. We see that the base of overdrive users is more heavily.
24:50
Concentrated in the higher income bracket considerably more so than in the full service area.
24:57
How does this align with Equity diversity and inclusion goals over drives and all ebooks for that matter are only one service the library provides but in our current climate many of the physical resources have been removed from the menu of services people can utilize usage is Shifting to resources available online and e-book usage can be one indicator of who is able to access the information available remotely.
25:21
In sites like this one. I thought provoking and certainly for a lot of questions given the current circumstances libraries needed to make decisions quickly and with very little time to prepare will strategies change.
25:34
How will I meet their goals around the operating conditions change so abruptly For now, I'm going to continue with this dashboard but keep those questions in mind and we will revisit this topic when we compare the pre and post closure overdrive user basis.
26:01
We can look at the other Graphics through the same ones comparing the proportions to understand whether a certain population uses a service more heavily than we expect.
26:10
Looking at the presence of children here in the middle.
26:13
We see a slightly higher proportion of We also have like the residents at the bottom will focus on the first length of residence bucket here 0 to 4 years. I like to look at this bracket because it can be indicative of the level of awareness of Library Services by focusing on this group. We can see whether new or relatively new residents are using the library. And in this case using eBooks on overdrive.
26:41
We see the opposite relationship here where the proportion of households in the service area with a length of Now, let's take a look at the panel on the right showing us the breakdown across the Experian Mosaic segment as Amanda mentioned one of the powerful aspects of the analytics is providing information on both Patron and non Patron households from the exterior Mosaic segmentation model. Well, we can use Library data to understand Patron usage within the library. We can understand a whole lot more about patrons by understanding what they do outside of the library and to be able to figure out how to meet them where they are.
27:29
The model is at the household level and categorizes American households into one of the 71 segments they have in the model. So we have a lot of granular detail here.
27:38
Then you would read this chart just like the other charts we see on the left, but there's an additional column at the end title Market penetration. This cone compares the patron household count to the base household count to give you a percent of households within each experience Mosaic segment that has an overdrive user. I like this figure a lot similar to the proportionality Concept in the other tables.
28:07
As you'll see this chart chart is sorted by the base population meaning that we sort the experience of a segments by their prominence within the service area rather than within the patron beef. It's interesting to see what the most prominent mosaics are within the patron base, even though they often do not align with the service area.
28:24
Yeah what this means is that the library is capturing certain audience is much more with certain services in this case overdrive ebooks while this concept is not new or surprising. It is definitely interesting to see who the library is able to capture better with the service. So let's take a look at the patron base using overdrive ebooks. We see that the top five Mosaic segments within the overdrive users are the ones off the statistic. It's representing 16% It looks like there's some kind of a filter. So let me just take that off.
29:00
Sorry about that.
29:01
Sorry for the technical difficulty representing 16% of Patron household colleges and cafes with 14% And consumers with 9% sophisticated City dwellers of 4% 4% These five Mosaic segments represent 47% of the patron base. We also see that the market penetration rates are very low for these five Mosaic segments the market penetration ranges from 5 percent to about 23% It's not surprising that the market penetration rates are so low as this is just a subset of period in the interest of time. I won't go into too much detail.
29:46
The overdrive user base just now that as a user of daily analytics you're able to login to Experian Mosaic portal to get additional detail on each Mosaic segment. So the first one was going through epic sophisticates, they are mature upscale couples and suburban homes colleges and Cafe are youthful singles and recent college graduates for me in College Community consummate because consumers are households is high discretionary income living upper-middle-class sophisticated lifestyle.
30:14
Sophisticated City dwellers are wealthy Boomer age couples living in cities and close.
30:44
Using this tab, we can visualize Patron households on a map of the service area to get a good understanding of where ebook users are located around the service area by visualizing patrons in this way. We can also understand if there are areas where featuring householder custard or if there are gaps and we see areas without Patron household on our map here. We see patrons tend to be clustered in certain areas and we see a distribution of non patrons reading a radiating out from some of those clusters.
31:12
This gives us a good idea of where overdrive users are distributed throughout the So now we have a pretty good picture of what was happening before the library's closed sort of a status quo. And now let's look at the dashboard examining users of overdrive post Library closures.
31:40
Starting with the patron measures measures tab. We can quickly see what patterns held or changed within the overdrive user base closure looking at estimated household income. We see a similar pattern where household income under seventy-five thousand dollars are not utilizing overdrive as heavily and we see an over-representation of users in the income brackets of 75,000 dollars or more.
32:06
We see a similar pattern for households of the confirm presence of a child seeing that these households use OverDrive more heavily than expected. We also see the same pattern of under-representation of newer residents using the service called closure looking at the distribution of overdrive users post colder across Mosaic segment. We see the same top five. We can also take a look to see how they are distributed throughout the service area.
32:37
Now that we have looked at the two user basis individually we can do some comparison to see what changed. Let's start with the patron measures tab.
32:47
We can compare the demographics between the two time period pre and post to see if there was a shift in the base of overdrive users and to understand who is utilizing the service more heavily. Was there a growth did we see a larger? I'm going to switch back to the slides now so we can look at some of the charts side by side.
33:16
The first thing to note is the total number of Patron households or households you had activity on overdrive during each time period and this case we would look at the panel in the upper right hand corner and add up the experience and not Experian Patron households to get the total number of Caesars household. We see in this case that the user base grew slightly so pre closer. We had 5,000 households.
33:46
Difference because the pre closure period was much longer than the post closer period we close our was about two and a half months and put closure was only about two weeks.
33:57
Now, let's look at estimated household income as we already discussed. We see a similar pattern during both time period what was the an over-representation of households with estimated household income?
34:27
And of household utilizing overdrive have an estimated household income $75,000 or higher nothing even bigger difference when we Circle back and consider that only 30% of households in the service area have an estimated household income in that range. How does that align with Library goals around Equity diversity and inclusion since the climate has changed what do libraries need to do to be able to meet these EDI goals. Well, why why gold or on EDI need to shift and save it based on?
34:56
What is now a available to patrons As we previously discussed having all Library services offered remotely automatically has a barrier to entry that patrons have a way to access the services offered.
35:09
Third what steps can the library take to remove that barrier to entry? Some libraries are keeping or turning on Wi-Fi is that people in the vicinity can connect to the network? Some libraries are even working to boost the signal that the reach of the Wi-Fi is extended.
35:24
in many libraries have 1,000 all of their Wi-Fi hotspots to ensure they are fully utilize some libraries are maxing out on There's definitely a lot of things to think about with the shift to having all Library services available remotely.
35:45
Now, let's compare the map the map from the pre closure dashboard represents the users of overdrive when the library was operating on a normal schedule with physical resources available. And when people around the country were able to move about freely now, let's compare this to the map close close closer did we see growth in certain areas is the distribution of Patron households across the service area of visibly different.
36:09
We see some growth in different areas of the service area were examining from a bird's-eye view looking at the full service area. We see a few spots with new feature in households where there weren't as many before there's one spot in the north kind of up here and there's one in the South as well. One feature of analytics is that you're able to zoom in on specific areas to examine them a bit closer and in more detail. So let's zoom in on a few spots that are dense with both patrons and on patreon first of all, look at that.
36:38
the map We see that the dentist area right outside of UC Davis has many users during both time period we can however see some shifts at the micro level on a neighborhood by neighborhood basis and the postcards are map on the right. You can see an area in the north area of this map where we saw a bunch of patrons pop up on the top of the post.
37:19
Let's zoom in on another section. Let's take a look at this cluster and the northern section of the map within the circle to the human eye. It doesn't look that different.
37:30
The dark side for Patron household is based on checkout volume and the higher volume from the longer time period but if we look at the in the same area So I think at this point that wraps up our analysis comparing the overdrive user base pre and post Library closure there our analysis we learned who is using overdrive eBooks from the library is operating normally and people were able to move about freely. We learned some demographic information about them distribution across estimated household income bracket presence of children.
38:30
We identified the most prominent.
38:39
We then learned about who is using overdrive ebooks after the physical Library location quotes and Library offerings are only available remotely. We saw that many of the same patterns held within the user base. So we did see a shift where overdrive users were more concentrated in the higher income brackets of $100,000 or more.
38:57
We also compare the two groups of users and saw that the user base grew we learn that there was an even bigger difference proportionately between the overdrive user base and the service area in terms of estimated household income.
39:11
We examine the map and saw where there are shifts and where you either household or located and we saw where there was group growth within the community.
39:19
So now what given what we learned I think there are a few key takeaways. It is important to examine both the pre and post Library closure time period as we saw in our analysis we learned a lot about the overdrive users even just by looking at users in the time period before physical libraries close and people were living their lives under normal circumstances comparing this user base to the post Library closure user base was even more interesting and added a lot of contacts to the current situation.
39:48
Facing another thing another key takeaway, you know understanding the users of overdrive both pre and post closure can be indicative of use of remote Services through the library. The overdrive is just one service the library provides remotely the user base for this service can tell a lot about who can and does access services available online. Now that the libraries are closed users of remote services are primarily through the library serving. Does this population aligned with the EDI gold of the line?
40:18
Very through the goals need to be Revisited in light of the new circumstances.
40:31
So what are some of the next steps you can take? The first thing I would say is to use your data. Now that most services offered are available remotely or online. There is a data aspect connected to each of those services use it understand it and learn from it. There's so much you can learn about how users are interacting with the library during this time just by looking at the data attached to each of those Services next. I would say to reassess your golden.
41:00
Strategies while operating under the current circumstances at this point. It is uncertain when libraries will be able to reopen their doors. And when that does happen what that would look like.
41:31
Lastly I would say to consider targeted marketing. There is also the possibility that current patrons are unaware of all of the services available to them provided by the library remotely. This could be the right time to consider targeted marketing analytics has a mailing list feature that allows you to segment your email address.
42:07
Some of the information provided on household includes things like household composition are their children in the household. How old are the children? It includes information on interest you they like to admit are they interested in Gourmet cooking do they like music? There is also information on things like whether households are likely to subscribe to internet at home.
42:28
Using this information we can identify populations who would be interested in many of the offerings the library provides remotely including online programming like book club knitting circles and story time.
42:58
That this you can then use to send those Charter Communications. If you're interested in learning more about this process, let us know and we'd be happy to help.
43:08
And now let's take some time for questions.
43:14
I had a couple questions that came through Lisa toward the toward the beginning of the webinar and regards to the data that was used. Can you talk a little bit about how an individual or where the individual would get the data from? I believe that came from overdrive. Yes, the data did come from overdrive. I you know as an employee of Gail.
43:38
I personally don't use OverDrive, but I know that this is something you should You can usually output from the marketplace. I believe it's called. I don't know if you can shed more light on that to a manic. I know you've worked with some people who pull the overdrive David to use and dealing with it. Well, I think the question came from can you share the name of the report that generates the transaction data?
44:02
I would have to check on that because I don't remember what it's called. Okay, we can get back with them on that. And then those are the only couple of questions that came in the chat, perhaps we can open up the webinar for live questions.
44:24
Yep, we're open for questions. I haven't gotten any yet. Okay, definitely can take more questions. Yeah.
44:39
Well while we're perhaps waiting for questions Lisa, I know that you know during this time you've conversed with, you know, several libraries about what it is that they're going through during this time and changes that have been made and so on and so forth. Maybe you can share some of you know, the Insight perhaps that you've shared or you know, just some advice that might be pertinent.
45:06
You mean in church in terms of like dating you said you're in terms of data usage. For example.
45:13
Yeah, I mean a lot of the libraries that I've been talking to especially the ones who are already starting to look at their data. They're doing something similar to what we are doing but not quite at the level of looking at you know, all the information that we get from Experian. And so a lot of the times it's you know, even just understanding the difference in usage pre and post the analysis. We looked at today does look at it at the household level or at the user level, but you can also look just to see if your circulation has changed significantly, you know, there are a couple ways to do it.
45:42
Of course there's Pre and post so understanding what your circulation was like right before closure and right after closure, but it's also important to look at the same time period last year to understand the seasonality and to understand what kind of changes you do expect to happen during this time period that's a good point about the seasonality to another question came in and I think it's more related to the segmentation portal some of the data sounds similar like a Bohemian or flower power. How do you differentiate between the two?
46:13
For me and you can certainly add your Insight on this as well Lisa, but because there are 71 different types. There are an actually 19 groups. There is some overlap within the groups perhaps there's you know, five types for group for example, and so there is some overlap there but the the demographics that they take a look at are going to be things such as income of an individual perhaps where they live Urban or rural whether or not they have children.
46:43
The type of house that they live in you know, these kinds of things so Bohemian and flower power. I'm sure there is definitely some overlap there but they do differentiate them within the various groups. You have anything to add on that Lisa. Yeah. I mean, I think Amanda's right there are there's a lot of overlap between them and I think that just considering how the Mosaic segmentation model Works.
47:07
They consider, you know 300 to 400 data points when they are trying to understand how to categorize His household and so, you know, there might be some some groups that sound similar like babies and Bliss and kids and Cabernet and I think that a lot of the times it's the fact that they're looking at so many different things and understanding which of those things differ are what's going to help you differentiate between them. I think it's also worth noting that the summary that I gave today were very brief, you know one sentence summary of each group, but if you go into the segmentation portal, they actually give you the information on all three hundred or so those data points.
47:43
They can go in there and kind of see what the nuances are and see what the real difference is our from a data standpoint. Yeah, and and just one more comment. There it is it is deep. So it's very granular information. So if you can understatement Amanda, but yeah understatement. Yeah.
48:03
Yeah, so so segmentation portal, I think they'll get an idea of that because it will talk about, you know differences in head of household income or you know, who what sort of Transportation individuals use their political affiliation, you know it cetera so it's pretty granular. But of course, there's always going to be some overlap as well. Another question is where would we find this on the website? I'm assuming the question relates to where would you find more information about bail analytics on the Gale?
48:35
Site what it's going to look at these please let me know but it'd be Gail.com / public that would be the website. So it's a dedicated Public Library website and you can access the more Link at the top menu and then click click on Library marketing and management. That's where you'll find information about Dale's data resources there.
49:01
And then another question here Lisa when you say adjust your EDI goals accordingly. Could you go into a little bit more detail on that?
49:13
Yeah, and I think that it's really just assessing the goal that you have identified in set for yourself around EDI and just understanding if those are still applicable I think that with Library closures and with you know, not just library look closing a lot of businesses in the communities and in the Fourth area is you know, we're certainly not operating under normal circumstances and the goals that were identified were identified, you know with very different circumstances with Library doors open with a lot of physical resources available with no a public service component having people available for reference or for any kind of any kind of resourceful help at the library.
49:53
And so when I'm talking about adjusting, I don't have anything in particular in mind, but it's really about assessing the goals that you have Kurt had previously identified and trying to understand if those are still applicable given the change in your circumstance.
50:10
Okay, if whomever ask the question in regards to EDI, if you'd like more explanation on that or if you have anything specific, please feel free to follow up a couple questions in regards to privacy. So I'll group those together. So in regards to the segmentation portal and privacy there and again Lisa feel free to chime. So basically those two services for Gail rrr.
50:39
Separate we've got Gail analytics and then we've got the experience Mosaic segmentation portal in which is available for you know for patrons to use now. It's integrated in Gale analytics in the sense that the segmentation tools are available, but how experienced you know, the data behind experience segmentation tool is not blended with the Gale Analytics tool. So all we have is the aggregated information.
51:09
In the segmentation information Etc. So from a general non Patron US population. We do not have access to granular or you know Patron address information from that standpoint in regards to Patron addresses and addressing privacy from Gale analytics again, everything stays in the library's hands. So you basically need to consult with your own private.
51:39
Two policies. I know those are ever evolving within libraries and many libraries might post something on their website saying for example, you know, do you do you allow us to you know, use this this address? For example for Market just direct marketing purposes for segmentation purposes or to help to better serve you these kinds of things. I think you need to go through and go buy your own guiding principles of you know, the the standards that your personal library has set.
52:09
In regards to that as far as veils perspective, we don't have access to any of that information and all of that is written within the user agreement your and anything to add to that Lisa. I think I just want to emphasize what you just said Amanda that you know, the biggest days with the library deal of course does not have access to if at any time. The only way we would have access to data is if you directly shared it with us for consultation or four questions.
52:40
And I think it's also worth noting that I've gotten this question in the past the way that we the way that we work with the data is that we take the data in the cloud. Of course, we take the data that you provide and we append on the data that we have from a from the experiences a segmentation. And so the data never leave that area. There's no access to it from us from Experian or from anyone else. It really just depended on to the data process and analyze that you can interact with it and then you were given back the custom dashboard.
53:08
So I think it's really important to just Emphasize as it never goes anywhere. It gets appended onto it gets a little bit and give you a way to interact with it. Thank you. Just another question here in regards to the overdrive data a user not necessarily being able to see how to obtain check out your check out level data. So just go ahead these for you to say something.
53:39
Oh, no, I was just going to say just clear. There are two pieces of information from from overdrive. So it's the check out information that's associated with like a barcode and then there's a separate piece of information and attached the the barcode to to an address. So there are two different types of reports there.
54:02
As far as the actual report that comes from from overdrive again, we can we can get Back with you on that but because we don't use OverDrive personally, we don't have the specific names of those reports. Basically, those are sample or dummy data. Basically that was that was used in the same format that overdrive outputs it so we can certainly get back with individuals. I'm sure there are individual that there are several libraries that use the overdrive tool.
54:39
We can certainly consult with them and get back with you on that.
54:48
Okay. I know we just have a few minutes left and I don't have any other questions as of yet.
55:01
see Not seeing any other questions. So it's I know you were sharing your you Lisa sharing your information on this next slide. So if people come with up with questions after this webinar, they're able to contact you. Yes, absolutely.
55:33
Absolutely.
55:38
Okay. Alright. Well, thank you very much everybody. As we had said we hope everybody is safe and healthy both physically and mentally through this time and certainly any questions that you have. Feel free to reach out particularly those individuals that had questions about the specific name of the overdrive report. Please reach out to me or Lisa and we can certainly get back with you on that.
56:06
Alright. Well, thank you so much Amanda and Lisa for that great webinar. Thank you very much for Hope for hosting this. Yeah, thanks and for our audience everyone who registered and attended today's webinar will receive a follow-up email tomorrow that includes a link to the archived recording of This webinar as well as a link to a certificate of attendance. We also put a link in the chat to a short survey. If you could please take a few minutes to fill that out helps us in planning future training.
56:35
Thank you again everyone, and we'll see you at our next webinar. Thank you. Bye.
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