okay everyone thank you so much for joining good morning good afternoon good evening wherever you are calling from today the favorite thing that both uh we like to do here is to meet with our customers and in today's session you're going to learn how to modernize omnichannel routing with advanced work assignment and this is part of our series live on servicenow webinars my name is Harriet Franklin and joining me today is prithvi yoganan before we get started I just want to talk about the Safe Harbor notice we're going to be showing you perhaps talking about statements that can be forward-looking please don't base any decisions of what you see based on timelines or products that we show that may or may not make it into the product um as I said earlier this is a series here's a QR code that you can click to join us for future webinars we also have meetups where you can ask us questions based on webinars perhaps we can have a follow-up meetup on this particular topic it's going to be jam-packed today a little housekeeping um please use the Q a tab to ask your questions do not put them in chat we're going to try to answer your questions all along the way and there'll be a little time at the end for your questions this presentation is going to be recorded and it's going to be on the community so feel free to post questions in the post on the community and we can all carry on a dialogue after this session you will be prompted for a survey and please we would love to hear your feedback on what we can do better next time as I said earlier my name is Harriet Franklin and I'm part of the outbound product management team for customer service management specializing in in the area of customer engagement and joining me today is prithvi yoganan and when prithvi presents he's going to give you a short bio of who he is and what area he specializes in okay so before we get started we have one poll question and we just want to know how are you routing your and assigning the work for your agents is it currently a manual process where your agent selects from an inbox list uh is it manual where we have a supervisor or a manager that assigns to your team are you using our advanced work assignment or do you have a contact center as a service or ccas solution please put your feedback into the poll we're going to give it a couple seconds or we can have everyone's feedback okay a couple more seconds we have a few more people I see a manual assignment is is one of the most primary way any others okay good all right Aisha we can end this poll and show the results okay um it looks like everyone is um assigning them to team members manually so this is going to be a great call for you because we have jam-packed information for you all right so today's agenda for those of you that are assigning manually I'm sure you're already aware of what the challenges are we're going to walk through a couple challenges highlight our key capabilities and components of advanced work assignment prithvi has a dynamite demonstration where he's going to show you how all these pieces work together and then he's going to go over best practices how do you get started what's the strategy that you need to set in place and then we'll follow up with a live q a so let's get started so when we think about service and the different people affected we have different personas the first Persona is the customer and when you have multiple channels an omni-channel strategy um customers want to communicate you communicate with your organization on any one of those channels it needs to be consistent service it needs to be quick it needs to be easy and customers want this resolved on the first time sort of advanced work assignment or ccast vendor then this is a manual process and it adds extra stress to agents because now they have to go and look for the work they have to manually assign and prioritize they're trying to be consistent across channels and then sometimes that work gets distributed in a way that's kind of unfair and then it's difficult to kind of route to the right agent because we we can't Route One experience so it's very frustrating for agents if as we saw in the poll a lot of these work items are assigned manually by a supervisor or a manager managers are concerned about customer satisfaction and they want to get the most effective work out of their agents and have happy agents if they're spending their time manually doing these assignments they'd rather spend their time on um coaching the agents working on more difficult uh escalations and they just want to eliminate that whole process of where they're manually assigning the work and so what happens is the customer experience is inconsistent we see the customer having longer wait times we see these items not being prioritized properly based on SLA oftentimes the customer is frustrated and calls back and and gets a new person to try to resolve their issue this results in of course low customer satisfaction and then there's really no way to really identify and look at who the VIPs are and prioritize the VIPs so all of these factors go into an inconsistent experience but if you take that experience and multiply it times all your customers and all your agents you can really see that this is a huge bottleneck in providing service to your customers so how can you take all these issues and fix them automate them and provide better service so here at servicenow we have capability called advanced work assignment and basically this gives you the capability to configure and Route the work coming in from customers to your agents based on skill capacity and availability and before you set all this up you're able to define the strategy what channels do you want to set up what cues do you want to set up and then you can configure assignment rules and really this allows agents to man manage their Avail we can have agents manage their ability and their present State and then just configure Advanced features once this is set up with things such as overflow or a better way to handle the customer experience with agent Infinity setting all these things up will improve your call center metrics it's going to increase your first call resolution reduce the average handle time and improve customer satisfaction so with that we've got a dynamite demonstration and I'm going to introduce you to prithvi prithvi why don't you please introduce yourself thank you have you hello everybody thanks for joining us today my name is and I lead the Omni Channel aspects of customer and Industry workflows Advanced book assignment is uh one of the products in my portfolio and this is a topic that I'm really excited about we launched advanced work assignment a few years back during method release and this has been an area of continuous investment for us so let's get started on this area um at the this is at a very high level what Advanced book assignment looks to accomplish there are different items within the contact center some of these items could be interactions like chat some could be tasks like cases and there could be other requests now all of these work items are waiting there to be assigned to an agent to work on in the middle we have queues which act as holding time to take these work items and assign them to the right agents who are organized within their groups and on the right hand side we have agents who are in their groups each of them have some work in their work bucket and have some spare capacity to take up more work so what advanced work assignment does is looks at these incoming pieces of work looks at the attributes on the work attributes could be things like what product does this work item relate to what region is this coming from or there could be any other condition that you want to Define depending upon your business needs based on these conditions AWA will route these work items into the appropriate queue and then once they are in the queue they are essentially in a holding tank waiting to be assigned and AWA makes that assignment action happen based on availability capacity and skills there could be scenarios where your primary group of agents are very busy they are not able to get to your customers really quickly and and attain your service level targets so in those scenarios we can bring in a black backup group of Agents through overflow to help get to the customer quickly we can also leverage agent Affinity way of looking at the work we can find Affinity towards specific agents and prioritize those agents we can also look at agent shift and based on the time left in the agent shift so I try specific specific age and store assignment so at a high level this is what advanced work assignment accomplishes with that let's talk about the demo let's go to the demo uh today during the demonstration we will look at five key scenarios we'll start with a basic scenario where we will route a chat based on agents capacity and availability as part of this we will also look at what happens in the agent misses a chat what happens when the agent rejects the chat and how do we capture the reason for rejection second we will look at overflow where we will bring in a secondary group of agents to help when the primary group is not able to uh you know help in a timely fashion during the third demo we will look at skill based routing where depending upon the skill requirements of the incoming work we would try to find an agent who has the right skills and address the customers needs a food demo is going to be around agent Affinity where we will look at the incoming work item itself try to find agents who have Affinity towards this income work item and prioritize those agents and finally it is in the fifth we will look at shift-based routing all of my demos today would be based on out of the box settings and minor configurations so at the end of the presentation today you all should be able to use this content and try this out on your own instances as well so with that let's dive into the demo um for our first scenario we have our agent John Jason who is logged on to the agent workspace he has made himself available on a bunch of channels including chat and he does that using the presence management module on advanced work assignment this business management module is completely API accessible which allows you to easily integrate with telephony systems so talking about telephony let's bring up telephony here and what you see here is on the right hand side we have open frame which is of CTI integration framework and within the open frame is a soft point UI that comes from a telephony integration partner uh this stock phone integration is integrated with advocacy assignment through apis for managing agent presence what that means is when I change my presence here on the telephony and I make myself away an API call is made to Advanced book assignment and the presence of the agent is automatically set to a way to synchronize it with whatever is there of that everything now this integration is also bi-directional where as an agent you can manage all of your presence from servicenow itself and that could raise an event send an event to open frame which could be listened by the telephony and drive the presence on telephony as well uh very important in contact centers where phone is normally a communication Channel and it is important to keep the two routing engines servicenows advanced work assignment and tell it means you know phone routing system to be in sync now with that let's go to the customers View so here's a customer George Warren the customer has recently bought a product and it's having an issue with the product so the customer is trying to reach out for support now it does that by initiating a chat and this conversation is presented by a virtually it's now for the purpose of this demo I'm going to bypass virtually agent and get directly to a live agent and I'll do that by clicking on this so at this point the conversation is getting routed to an agent let's go to our agent one um the we also have one more agent in our contact center agent two uh since both of them available and they had you know equal availability without without it to agent two for the purpose of this demo I'm going to reject this chat and say I'm busy and when the agent 2 does this that reason is logged in the database so if agent 2 is rejecting a lot of these chats the supervisor can look at it and then have a conversation with the agent now at this point what happened is the chat went back into the queue try to find the next best available agent and we see that in God's route to agent one we have some information about the chat itself we see the account and contact information on the chat um and upon acceptance the chat panel shows up on the agent's UI I can as an agent I can respond back to this using uh quick responses what you would also notice is this chat is packed up by an interaction record uh interaction is a key record in servicenow it represents any conversation on servicenow irrespective of the channel so you might be having a conversation over chat or it could be over phone or over SMS or Whatsapp every one of those conversations are modeled as interaction Now by having a single interaction model or uh you know data model we are able to drive consistent experience for agents across all these channels even from a reporting perspective this drives consistent experience for supervisors and executors because they don't have to go to 10 different objects to get their reports interaction is that single place to go now coming back to the experience itself interaction has some pretty interesting items on it this customer sample which comes with two key tabs customer information and customer activity the customer information tab shows some more details about the customer like their contact details some escalated cases that may have been filed um other conversations that they may be having and customer activity tab shows some of the recent knowledge article views the portal activity work orders cases interactions Etc so this gives you a holistic view of what the customer is has been doing and your relationship with the customer again both these staffs are completely customizable so depending upon your business needs and your unique business area you can Define these these tiles and have those tiles surface on the customer information tab uh search on the right hand side is contextual which can help you drive knowledge articles surfacing knowledge articles looking at past cases similar cases Etc and this experience because it's all centralized on interaction management is not applicable only for chat it is applicable for all channels so if you have a phone agent the phone agent will also see similar experiences on a phone call so what you just saw in this demo was we had a customer who initiated a chat from the portal we had a simple routing rule there for routing this chat into the right queue it got routed into the customer service chat queue and at the time of assignment we looked at availability and capacity we had two agents in our primary group and we chose one of those agents to make the assignment now let's talk about how to configure this you can do that using four simple steps number one is what to Route this is where you will Define your service Channel second is way to write way to Route which is where you will Define uh the queue thirdly we will do assignment we'll Define our assignment strategy and finally we'll also set some key aspects that drive the agent experience now under each of those four buckets we have a few items that we will take care of as part of the first topic which is defining the service channel will configure the object that needs to be routed second is defining the queue which is where we will tie the queue to a specific service Channel we will also Define the routing rule under which a work item gets into this queue we'll also Define the Sorting order um sorting order is an international concept on the Queue typically when you look at a queue you think of Q as a first and first node mechanism whereas at service now our philosophy is uh it doesn't have to be just personal personal you can sort items based on any attribute of the item itself example here is you can sort it based on customer status so if your VIP customer comes into the queue even much later at the time because there's a VIP customer you can automatically pop this customer up to the front of the queue the third part is assignment strategy where we will choose one of the two available algorithms most capacity or last assigned we will also optionally enable auto assignment and finally we will look at the inbox card layout and Def and the agent preference States so let's look at these configurations for this I'm going to go to the admin View and navigate to service channels now chat service channel is what we were looking at as part of this demo so let's get into that service Channel what you see on the top of the screen are some basic information about the service Channel uh we also have the table that the service channel variates to chat as an interaction so this service channel is tied to the interaction people now based on the table selection itself be automatically populate the assigned to an assignment group aspects of this Channel and we also have additional condition where type is chat what this means is any inter record in the interaction table where type as chat qualifies for the chat service Channel you can optionally also select inbox alert and message alert audio that will be played when a chat comes into the agency inbox or a message in the chat comes to the agent going further down in the configuration we have default work item sizing this determines the size of each chat what one means here me is every chat is of unit 1. the default capacity is the number of chats an agent can handle simultaneously so this configuration states that each chat is of one unit and each agent by default can handle up to three checks now of course not every agent within your contact center is going to be equally skilled you will have a few newbies who may be able to serve less number of chance you may have a few experts who can handle more chance and you can do that override in this part of the URL you can individually select agents and override the capacity at an individual level coming to the utilization condition this determines the the criteria under which a chat comes towards agents capacity as you see in this configuration with set state is not one of close complete or closed Brandon with this what would happen is when a chat moves from working progress to closed complete which is where the chat is getting ended um the age of capacity would be freed up and the agent would be available to take up the next chant moving to other sections of the configuration we also have inbox layout this is what determines what the agent sees on the card when the chat is routed to the agent's inbox the contact chat layout is what we were using in our demo and this has a very simple condition the condition here was contact is not empty and when that condition was met we showed the short description contact and account for the customer now we saw that in our chat every chat is of unit 1. but you know depending upon the complexity you may want to override that as well this is very relevant for cases as well so not every case is going to be of you know same size or scene complexity So based on examples like you know is this an escalated customer is this a critical issue and based on these attributes on the work item itself you can override the size this helps in adjusting the utilization of the the agent correctly so let's assume that an agent has capacity for taking up five cases it could mean five simple cases all of size one or if you have complex cases of size 2 it could mean two complex cases and one simple case so depending upon the size of individual cases the agency utilization will be adjusted accordingly the second part of our configuration is queue computation so let's go to the cube now the customer service chat queue is what we were looking at in our demo the upper part of the configuration here is basic details about the queue uh this queue is tied to the chat service Channel and this is where you would Define your condition under which a work item would be routed into this queue the condition can be simple in which case you would have a condition Builder to define the condition or it could be Advanced where you would have access to a script block using which you can script your condition we had a very simple condition here scrolling further down is you would see assignment eligibility please ignore the second entry here for a few minutes we will come back to it when we cover overflow let's look at the first entry here what this entry States is when a chat is available on this Queue at zero seconds this group the customer service support group is eligible to receive work and the assignment happens using this assignment rule so the moment a chat comes into this Queue at that very instance any agent within the customer service support group would be eligible to receive this chat and the assignment would happen through this we look at the assignment rule in a second when we go to step three of the configuration let's look at other parts of the qualification in the meantime work item sort order is where you will Define the Sorting of items within this queue like I mentioned it doesn't have to be just first first out in this case they saw a sorting based on customer status and the timestamp you can add any number of attributes here and order them think of them as simple Excel sort the third tab here is post chat survey so you can optionally have surveys and when a chat coming to this queue ends the customer would be offered a survey that is configured here in this section we'll come to agent Affinity in a few minutes later so we covered step two in our configuration let's go to step three which is our assignment rule so coming back to our assignment eligibility the middle section is where we have our assignment Rule and this is what the assignment looks like the first thing we would do in the assignment rule is choose our assignment algorithm which is either last assigned sh Lee without Robin or most capacity which routes work to the agent who has the most squared capacity uh about other configurations let's look at rejection handling first uh during the demo we saw that the agent had the option to either accept or reject the chat if you don't want the agents to have an option to reject at all you can do so by unchecking this this will make sure that the reject button doesn't even show up for the agent we also saw that the agent had about 30 seconds to accept that chance and that is driven through this part of the configuration if you uncheck it a timer will not be enforced we normally see that for real time channels like chat you would have a timeout with us for long running tasks like cases you may not want to configure the timeout or you may want to have a longer timeout optionally you can also set agent's presence when the timeout occurs example if you have an agent who is maybe distracted or maybe has gone on a break and forgotten to change his status accordingly you can set the presence automatically here so that point what will happen is when the chat times out the agent's presence would automatically be set to away and that way no new chat would come to the agent's inbox going to the auto Health assignment handling now we saw that the agent had accept ad reject option we talked about how reject option can be disabled but what if you want to you know not have the accept option also what if you want to just Auto assign you can make that happen by checking this setting that also brings up two additional options for you around display the display can be inbox card only in which case the work item would be assigned to the agent but an inbox card will show up with an open Button the second option is Inbox card and workspace Tab and with that when the assignment happens there would be a card in the inbox with an open button but we would also automatically open the relevant tab on workspace in background so consider chat a chat the new chat comes in and the auto assignment is enabled the new chat will automatically screen pop on the agent's workspace we will cover skill handling and shift handling in a in a few seconds so that covers Section 3 of our configuration now let's go to section 4. we already talked about inbox card layout let's talk about present States the present states are broadly categorized under two key areas a state that helps you assign worker state that helps you not assign work uh the former criteria is where available comes into picture the latter criteria is where Breakaway offline Etc on situation you can have any number of present States and also assign these present states to the right agent um in their group now when you come to this configuration uh you can select what most service channels that are relevant to this present state the short Channel checkbox also enables the agent to manage their presence granularly on each of these individual channels so that concludes my first demo now with that let's go to our second demo which is around overflow overflow is a scenario where your primary group of Agents may be very busy because of the spike and incoming requests and they are not able to address the customers request in a timely fashion when you're not able to attain your target service levels you may want to automatically bring in a secondary group of agents to help out and that is automated through overflow so let's look at a demo for that now for the Overflow in addition to my agent one let's enter here that the agent one was working on um and agent two I also have agent H3 the agency is also available and this agent is part of the secondary group so we'll again go back to the customer's view we will start a new chat and at this point again based on a previous configuration the chat will be routed to one of the agents in our primary group could be agent one could be agent two so it goes to agent two um as part of the scenario we're trying to simulate a where both the agents are very busy in order to do that I'm going to reject this chat and say I'm very busy this makes the chat go to agent one and we will do something similarious similar here also we will reject this chat at this point the chat is back into the queue since both the agents in primary group are busy the chat is still sitting there but at 45 seconds which is what we have configured for overflow we will automatically bring in the secondary group into picture agent 3 is part of the secondary group and she should receive this chat at the 45 seconds time which is going through the countdown of that 45 seconds which would have that chat any moment and there we go so the chat goes to agent 3 who is part of the second recruit agency receives the chat and has a conversation with the customer so what we saw here was exactly like before we had the customer initiate a conversation from the portal the chat was routed into the customer service chat queue as before we tried to assign it based on availability and capacity but at the time of assignment we realized that both the agents are busy they have uh they're working on the full capacity so the chat weighted in the queue for 45 seconds and at the 45 seconds mark we expanded the pool of agents to include a backup group and at this point every agent within the largest you know primary group and the secondary group is eligible to receive this chat so in this example we just introduced one group at 45 seconds it doesn't have to be limited to one group you can add as many groups as you want it also doesn't have to be just one level of overflow you can have as many levels as you want meaning you we had one at 45 seconds you could wait till one minute and you can add one more group and so and so forth so by doing that you're expanding your pool of Agents whom are becoming eligible to take up this chat and thereby you are improving the probability of getting to this customer quickly uh this is a Heidi differentiated feature and very unique to how we handle overflow what you might have noticed here is we are not creating a new queue for handling overflow the stat Still Remains in the same queue and then gets routed to the agent uh based on their availability this is very different from what a lot of our competitors do a lot of competitors force you to create a new overflow Cube for handling overflow there are two key problems there number one you have a proliferation of queues too many cues to manage second your queue statistics are not pristine anymore because this chat has spent two minutes before getting to an agent and not just the 15 seconds that it has spent in the latest queue but keeping the chat in the same queue we are doing number one uh we're using the number of queues you need thereby simplifying the management of the queues and number two the queue statistics also remain pristine now in terms of configuration this would be done at the queue level so let's go back to the admin screen let's go back to the queue we are the customer service chat queue and if you scroll down this is where we had configured our overflow so at 45 seconds mark we brought him a backup group and which means at 45 seconds both a primary group and the backup group were eligible to receive work from this queue like I mentioned it doesn't have to be just one group you can add as many groups as you want it also doesn't have to be one level you can add as many levels of overflow as you want so that concludes the second demo let's go to a third demo which is skill based router now there could be scenarios where depending upon the attributes of the of the work item itself depending upon the customer profile you may want to um you may have specific skill requirements to serve this piece of work now in under those conditions you will need the right agents with the right skills to take up those work which is for skill based routing addresses so for this part of the demo I will go to another customer we have Michelle who is our second customer she is based out of pain and Spanish is her preferred language and we know that as because that information is in her profile so when she initiates a chat we automatically add Spanish as a required skill to any chat coming from Mission now in the agent profile again we have both of our agents in the primary group agent one and agent two uh the agent one has Spanish in his skill profile agent 2 does not so for the time being I am going to let agent one go on break and the expectation here would be when Michelle initiates a chat the chat would remain in the queue because agent 2 doesn't have the right skill but the moment agent one comes back the chat should get routed to agent one so let's go back to Mission and we will start a new chat here again I will bypass virtual agent and try to get to a live Asian foreign [Music] and exactly as we expected though agent 2 is available it didn't get routed to agent 2 because the agent doesn't have the right skill let's go back to agent one and bring him back at this point the moment the agent becomes available the chat is offered to this agent because this agent has the right skill set and the agent goes ahead and accepts question so what you just saw was um we had a Spanish customer who initiated the chat in addition to the regular attribute we also added a skill requirement uh Spanish was a mandatory skill on this chat we routed into us the same queue we didn't create a separate queue for our Spanish customers and at the time of assignment in addition to availability and capacity we also looked at skills we saw that we had two agents in our group the second agent had Spanish and SQL profile and we went ahead and made that assignment to that second agent even though that agent may have had more work in uh in their on the bucket than the other agent uh this is again very different from what you will see from a lot of our competitors our skill based routing is completely declarative in nature a lot of our competitors do uh make you choose between skill based routing or queue based routing we believe that queues are extremely important in the overall framework of routing it is extremely valuable for our customers so we don't force our customers to make that difficult choice secondly a lot of our competitors also force you to create a separate queue for each skill combination now think of a scenario where you may have multiple skills they may be language skills they may be product related skills they may be you know skills related to escalated customers when you define queues for each of those combinations you have a large number of queues which are very difficult to manage so unlike all of those they make it very simple here the queues and the skill based routing is completely declarative and you don't have to create additional cues for handling skills the same framework can be used for sentiment based routing also sentiment is an attribute on the interaction if based on the initial conversation with the virtual agent if we realize that the sentiment is going negative we could use that indicator to add additional skills to the chat now in this scenario we could add custom manager as a required skill and at the time of assignment we could find an agent who has the right skill for making this assignment in terms of configuration let's go back to the admin View let's go back to the assignment rule the skill handling is where we would enable skill based routing so by enabling the first checkbox you could enable skill based routing and if you have mandatory skills and you want those magnetic skills to be enforced you could check this checkbox and that will enforce mandatory skills uh the combination of overflow and skill based routing is extremely powerful when you make the assignment to route through the assignment eligibility you can do the you can select your assignment rule at the individual entry level meaning let's say for first 45 seconds you want to make sure that you have the agent with the right skills but then if 45 seconds have passed you may want to relax your skill requirements and find an agent quickly you could make that happen by relaxing relaxing your skill requirements and having a different assignment rule in your overflow so very very powerful in the interest of time I will walk through the the fourth and fifth demo um we will not get into the incidence I'll walk you through the configuration uh agent Affinity is where you want to look at the work item itself and try to find Affinity between the agent and the incoming work we offer three flavors of affinity uh one is the history history based a purity where you can look at the history of serving the customer look at the agent base find the customer agent who has served the customer most in the recent past and prioritize that agent second is related task based Affinity where if you know that a given chat is in context of a case may be the best agent to take up this chat is the agent who is working on the case so you can prioritize that specific agent over other agents uh for assignment the third flavor of the sign Affinity is uh account team responsibility where if you have a named account Personnel for a high value account you can prioritize that agent over any other agent for making the assignment now in order to configure that it's a two-step process let's go back to the admin screen on the advanced work assignment you will see Affinity rules this seems to be running a little slow let's go through the experience and then we'll come back to the configuration so what you will see under Affinity is we would route the work item into the same queue uh we know that this chart is in context of this specific case so at the time of assignment we can look at the related case on this interaction in our agent pool we see that we have an agent who is currently working on that case and using related task based Affinity we can assign it to the specific agent second player is account team responsibility based Affinity so in this case if the first station is not available we can look for the named account personal for this I value account and prioritize that agent for taking up this chat the third flavor is historical Affinity so we may have an agent in our pool who has served this customer multiple times over the last you know seven days or 15 days or 30 days and we can provide as such an agent all of these Affinity rules can be used individually or in combination to drive customer satisfaction quick responses so coming back to the Affinity rules the Affinity rules have three flavors so the first thing you would do is configure your Affinity rules it could be based on accounting responsibility where you choose the responsibility but history will choose how back in time do you want to go or related task in which case there's no much setting to do now once you configure your assignment your Affinity rules you can go to your queue and under the agent Affinity section add these Affinity rules you can use them in combination so that way uh depending upon which of those three personnels are available you can prioritize them our fifth scenario is shift based routing where in addition to the regular working you can also look at the agent shift look at how much time is left in the shift and prioritize the agent based on your need so in this scenario we can we see that the fifth agent has the most time left in his or her shift and we can prioritize that agent over other agents now in terms of configuration this configuration lies on the assignment rule let's go to the assignment rule and you will see a section called shift handling by checking this checkbox you would enable shift handling you can have the agent sorted based on leash time left and shift for most time if you want to add additional constraints like you want the agent to at least have 30 SEC 30 minutes for him or her to even be considered for assignment you can specify that and you can also specify if the demanded time should be in one continuous chunk uh or can it be distributed across the entire day this does requires Enterprise q and access to servicenows Workforce optimization solution so at a high level these are all the different capabilities that AWA enables we have a lot of high value highly differentiated patent capabilities that drive customer satisfaction into csat and improve agents utilization we covered a lot of these during the demo the supervisor experience isn't something that we didn't cover but I would highly recommend looking at some of our earlier webinars on Workforce optimization solution to learn more about this topic with that let's talk about some best practices uh when you are defining your cues and your assignment strategy um our recommendation is to start thinking about the reporting needs and your support strategy and that will inform your queuing and assignment strategy there are a lot of different patterns that we've seen uh in our customer base one of those patterns is geo-based support this is top typically relevant to customers who have products which require similar skills from a support perspective example here are companies and logistics companies and media streaming Etc now for those customers for those scenarios recommendation is create your cues based on your region uh for of course you're going to have regions where you have multiple languages and for those multi-dilingual regions model your language requirements as skills add the skills to the right incoming work item assign those skills to the agent and have your agents in the groups along those geographical lines you can also have product skills wherever product skills is required as you can see in the illustration Below on the left hand side you have chats of each of some of them have language skill requirements some of them have product skill requirements also and they're getting routed into the right geographical queue and getting assigned to the agent uh while keeping the skills in mind second pattern is product based support this is typically relevant for companies which have complex range of products each product requires specific skills so there our recommendation is please create your skues based on these product areas and you know leverage language skills wherever it is required now they could be product areas where skills where expertise is interchangeable now in the scenario of the illustration below you can see that consumer electronics chat uh may be handled by Appliance chat group as well so you can use overflow in those scenarios where apply as chat group can come in and help out consumer chat consumer electronics chat group if they are not able to meet their service levels now uh you may also because jio is not being considered you are not having geographical queues here you may also want to look at shift-based assignment or to find an agent in availability in the nearest shoe or where the shift is having an over with the customer's time a third pattern here is customer tier based support which is where you may have tier-based queues you have a tier for your platinum customers time and customers and gold customers now in this case because your platinum customers are most important and you want to get to them quickly you can have two levels of overflow Diamond glue is the first envelope overflow while the Gold group is the second overflow your diamond customers may be your second most important in which case you will have of course the diamond group being the primary group but the Gold group can have and can serve as the Overflow group again depending upon your need you may want to consider shift based assignment as well to find an agent with the shift matching your customers needs now in terms of channels um yes it is super important to have a basket of large number of channels you want to meet your customers where they are on their most Preferred channel uh but it is also very important to deliver consistent experience across all those channels so our recommendation is start simple start with a few channels absolutely Master them and then gradually expand your portfolio of channels to deliver that same consistent experience on these newer channels that you have been delivering on the previous channels too in terms of service channels when you are defining them please keep interchangeability of work in mind for example if you're an insurance company you may have different types of cases like claims cases or dispute cases um if the same agent can work on both the type of cases you may want to model them as one single case service Channel whereas if there are two different agents you may want to model them as different suggestions messaging channels you may want to combine them in one single service Channel because the same agent might be able to serve on WhatsApp online or Facebook Messenger the skills are fairly interchangeable across those channels asynchronous interactions are the way to go but when you are embarking upon this journey please evaluate your agent training your reporting needs um reporting is fundamentally different for the asynchronous conversations also think about Geo uh what channels do you want to support uh in each year managing agents manage their capacity based on their expertise they reward the skills Etc whether whether it makes sense these two Auto assignment uh you can also you know use Universal capacity management for your Blended agents when handling more than one channel at a given point of time um Universal capacity enables you to split their capacity across multiple channels and have just one bucket across all those channels uh if certain items are complex in nature use work uh sizing for sizing those work accordingly and managing the agent's utilization accordingly absolutely enable CTI integration this is important when you have two different routing engines in play the C the phone's routing engine and service now shouting engine Workforce optimization is an important capability and you can manage a lot of Agents monitoring and coaching Etc using this product talking about CTI we talked about two different routing engines and they need to be in sync and you can make that happen using AWS presence apis and the events that AWA emits which can be used by CTR for driving presence on telephony in order to make that happen we offer five events with these payloads and these could be used for driving this integration in a seamless fashion so the lot of great content important resources you we have additional resources for you you can look at our documentation site we also have a white paper on AW implementation our YouTube channel has a ton of videos which can also help you get started and help you learn more about other adjacent product capabilities um with that we come to the end of our presentation thank you for participating thank you um for being with us and spending this time with us if you have any additional questions please post those on our community page we will answer those there on the Community page thank you very much thank you everyone for staying on all the way through we would like to hear your feedback on what we can do better next time in the survey I also want to really thank Chris V prisby was one of the architects of this feature and as you can see we've got patented technology and differentiated features and please come back to this and try this in your own test site he's got all the steps there for you you can replay them in the video and our goal here we notice that most people are using the manual process our goal here is for you to use the functionality and take advantage and relieve some of these bottlenecks for your customers and this advanced work assignment will be something that uh you'll your organization and customers will benefit from so with that please take the survey thank you everyone for joining today and please catch the replay