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as bein said I'm the VP of cough a drift I was prior to that the VP of goth at a segment a number of other likes ask companies have been doing SAS and most specifically b2b cells for the past the sixteen years now as I started on b2b online sales in 2004 Apple so that brings us back quite some time so people call me gee obviously French and there's there's really three things that I try to focus on one is SAS second is like yeah like self-service sales automation and growth experimentation those are the three things I really like to focus on and I think if you often people ask me what's my job as the VP of growth so I thought about it a lot and so my job the way defiant is I create competitive modes through great marketing great lifecycle marketing so that you can compete and destroy your competitors through insane cack meaning a low CAC and today we're going to talk I'm going to talk about a sales automation all right I'm gonna talk about sells assisted businesses where you have a sales team that sells team needs demos and I'm gonna show you how we can push that say the the automation to new heights to new levels again to bring that that CAC down so if you think of that kind of business you ask yourself well what's the job of an SDR right I've been working for SG owes a lot I actually will share my life my wife is a salesperson so I know such people quite quite a bit and and when I talk to sales people and especially as the odds you're gonna think well they do a couple things data collection and entry okay they do lead qualification and they book meetings for AES it's not a great job to be honest right and why is that actually becoming a worse and worse job it's because they're facing low and lower conversion rates what can the the rate of booking a meeting family is going down right and they're incentivized to actually have mo meaning so how do they respond as humans right well they increase volume right they send more emails more out down emails right and so when you think about that you ask yourself what are humans not good at right and they're not good at maintaining a good quality while the volume increases and so that's why we are getting a lot of spam we're getting a lot of spam has found us as buyers because these as deals are trying to get those meetings right it's if you think if you take it a step back and you think of like how that model works and why we're having that issue if you look at that curve you can have a lead ya representing like a leader the little chat bubble because I do live chat that's profitable if the lifetime value of that lead is greater than the cost of selling makes a ton of sense we could have a lead which is unprofitable right because the cost of selling is is greater than the value mostly because that Lee does not convert right the problem is that you don't really know which is which before you engage the sells effort right before you actually have your entire sales motion your marketing motion that's there right so you're engaging the cast first and you see the potential value later right and that sucks right and so if you actually look at your landscape it looks like this we have like all of those potential leads on that landscape and you'll figure out where they are right and so as a marketer you have your founders like how do marketers react you can you push your marketing team say hey I want more profit I want a better cost of cost of acquisition do something what do they do they do this they bring the cost of selling down because they don't know which ones are gonna convert right what does that mean it means that the entire experience is gonna get worse because they have less budget per person they're going to spend less which means the emails are gonna get worse if you send gifts they're gonna get worse if you do events they're gonna get what everything is gonna get worse so you can bring the entire cost bolete down and so what they do is that's my fault I'm a marketer I did that right I created that messy world where quantity is bigger is more important thing than quality right so couple questions here who's a cruise assess value who buys ass here I imagine almost everyone right let's see your show of hands yeah okay cool who enjoys buying cess who finds it too enjoyable experience I'm nothing a single hand here just problematic right because most of us actually sell sass and we don't enjoy buying it too right that's kind of a schizophrenic problem with you all right and you think it's just us you know it's fine we're founders whatever it's just us it's not the world right world is great 2015 Forrester survey shows that 53% of b2b buyers don't want to talk to sales reps you think gee that's 2015 when 2019 now things are getting better right yeah so 2017 is 68 percent so that trends going up so they really don't want to talk to us that kind of sucks and if you look at another number 70% of between buyers start with a generic search query they do not search for your brand right kind of makes sense but if you think about it they don't trust your sales reps right they don't trust yourselves to give good advice I'm not even talking unbiased advice I'm just if you talk of good advice right very much the same way you probably don't go to a hotel's website before booking hotel why'd you go to TripAdvisor I go for worse when you go to go to Yelp you go and go for like crowd-sourced advice right so let's go back to a first-ball what's a good way to handle large volume of low frequency events frequency of those events is conversion into demos it's code right that's a good system right what's good at creating a consistent experience high-quality strands because it's also code alright that's the word I'm seeing is a world where data and engineering is eating cells and I like that I'm going to show you how we do it so the first thing that we did is we partner the company called Matt could do and disclosure here mastering advisor there to build a reads going model and you can think that's easy we have that I have that in market oh I'll show you why it's pretty unique right but the leads before we go there the leads going models very efficient right we're able to predict about 80 percent of future business within 16 percent of our leads so it's a good concentration of other quality okay so what does that mean it means if you look back at that landscape at the moment we get all those leads you're able to actually place them on that curved you know which ones will be profitable and which ones won't all right once you know that and say hey gee I'm just gonna engage on those that are out there all right I'm gonna ignore all those that are down and say wrong wrong wrong wrong you should do this usually actually split multiple experiences at multiple costs so that you can have a serve service at a lower cost right so you make profit and maybe an enterprise model at a higher cost that makes sense we all have that but that this is the few of why we have those kind of like brackets and if you're good you don't stop there if you're good we actually build this right where you have as many experiences as possible and so the reason why this is important is because where your competitors will have a very linear budget and they're gonna decrease the experience if you have that you're able to have an experience that is finely tuned to the budget through the revenue you will get you have in the future which is you can have a better customer experience than your competitors which means you will close and they want alright and if you're thinking this is crazy think back to how b2c operates in bit you will have a lot to learn from B to C alright we're just building the right amount right were just spending the right amount on each potential customer all right it also means we're not gonna span people if we know what we're not convert right the reason why I talk if b2c because that's exactly what retargeting and our TV real-time bidding works in b2c world right when you see those ads from Amazon or any other consumer website they are making a bet that the cost of displaying that ad is at the conversion rate is cheaper in aggregate then losing yourself right and so there's profit to be made there that's exactly what we're doing but we're just applying it to be to me so if you look at your funnel where does it start you think it starts here when people land on your website that's the most common definition of a funnel people count your website's some of them will sign up some of them will convert and so on and so and so on and I'm thinking well as we said code is moving up the food chain and so what happens before then on the website we talked about those buyers not wanting to talk to you those buyers going to like find other advice and going on a generic search query I found some data from Google as a 2015 Google insights survey b2b buyers they do 12 searches before engaging with a band 12 that kind of makes sense you know I probably do 12 searches before going for on a hotel in in you know in Lake Tahoe so like when I buy for like a three thousand per month like subscription for my business I'm a hundred percent a neutral soldiers of course all right so what happens there well there's this little model that we have constructed to understand the behavior of visitors right if you think if I a b2b buyer and their life cycle there is the fit the the fit model the leads going model that is what we called about the the belief all right and so the belief is for Springs I sell live chats you might have found a state well I've got this good yeah I think we should have live chat you don't know that you should buy drift yet at least but you have a certain belief about live chat technology all right so that brings you on a scale of 0 where a 0 is you don't convert and 1 you do convert the hundred percent rate right might bring you 8 to 20 percent and then you're gonna visit to a party websites okay and discover the markets you're gonna maybe visit my what sites you may be going to a self-discovery of my feature pages maybe you're gonna sign up for trial maybe you're gonna even talk to myself after that or just gonna get my inertia emails right all of that is a behavior curve that we can analyze you can model right and if you look at leads going models most of the time and your BR your analytics you start capturing data after the trial you start I'm doing the leads scoring at the moment of sign up right and that's good it's better than not doing it right the put all of that is that it means or marketing or reaction to push people from like maybe eighty percent over one happens quite late right it happens they're actually right and your marketers gonna say well we'll do some arm no reengagement campaigns will ascend them offers by email or retargeting but like the thing is that that curve goes down extremely fast I've analyzed that curve in many startups it drops like a cliff right and the reason why that is is because there's a discrepancy between your marketing and your product your marketing always says that it's better than what the productivity is all right that makes sense it's called marketing for a reason it's also because usually there's some kind of setup and you're not gonna put in your feature pages or in your ads hey sign up then connect the apps or like invite your friends or whatever it is if you need to do to get the value there's no immediate value so people sign up they would they just saw the messages about the great value and now they go they need to go into the setup alright and so there's a cliff alright and so you try to bring them back most of the time the goal is there but your actual campaign effect is there what we mean by that is that the injection of momentum is insufficient to get them to convert alright and of course you're not gonna give them a Tesla because otherwise you'd be in a negative margin territory if we model that again so we talked about lease going so blue pots that's the fit prediction the orange pot is the behavior analysis what we don't do is the understanding of when that curve is at the highest moment when should we push right and how can we push exactly at that moment so the costs of the momentum injection is the lowest possible and what we've done or what I'm going to show you now because this talk is about intense and predicting the future is the ability to understand the buying signals in those twelve searchers before they hit my web sites do you understand the shape of the curve before my competitors so how do we do it with intent data so if you go back to that curve you expand the discovery of market look at those twelve searchers and you find that well we were scoring after the hit on the website we were enriching of klebanov mad kudu but all of those places all of those companies the companies that can buy intend data from and I can actually move my scoring through the very first intent hits so for those who don't know G to crowd you to care there's a kind of the Yelp of SAS software and they sell the intent data and we'll show you how and all of those companies are just a fraction of those that sell intent data on purchase behavior and we actually run scoring models based on our trials but we run that on the intent before people come to us so a couple of things that goes into ten data our data in eyes same as hdhd data they sell great web technics what that means that they tell you which technologies are installed on a given website so you can say hey who has intercom my computer installed alright when have they installed it when did they remove it I can create some of those campaigns I love some of those campaigns and they hate them because I'm able to send a lowball offer to our companies that have just sign of intercom or companies that I know will renew because they've installed it ten months ago right say hey you discount in your price sure but I'm creating in an ml churn for my competitor right because either they take my offer it's a hot attention or they just don't take my offer but they leverage it to get a discount so for the cost of an email I'm a creep I'm actually creating a mulcher Jeju crowd talks about it that's a typical cheetah Club page you see my logo here each time that's my logo I'm able to get the ping there's a great API and I get a ping to know which company has viewed either the category page my page my competitors page can see here for informatica big french company you can see they have seen intercoms and this chat live chat and the call of the bubbles represent a different visitor so I can know the number of unique people over time so we actually have a mock ml modeling to understand like what the curve is of the intent over time this is there's a buying process happening here it's like you don't need to be a good genius sales rep right producthunt you all know pollutant as an API to know who has voted your product or competitors product very great insights Linden we scraped Linden to find who has voted or commented on all posts all the posts of other influences and we follow up automatically say hey we saw the engagement there BOM ba ba ba lets you know which companies are reading about what topics they leverage the demand side marketplaces for advertising for that sem wash you know the cost of the clicks so the spend on AdWords of specific companies you go back to informatica campaign 27 bucks per click on data integration all right I know which pages sending that traffic to so I can leverage that predicted let me know job postings so for example in our case we sell technology the best moment to sell technology when a senior executive is hired and wants to enhance a budget and wants to do some change at some one best moment alright and so knowing when that happens it's critical for us save data with average that to find some of our champions who are moving to another account while we they're not the customer and so we track that automatically there's like in tech there's like a 15% turnover rates you over you're like why do tech people go in tech so it's not a surprise that sending them nice headset in the first couple weeks saying hey we used to love you we still love you think about us works great so what do we do with that data right well if you go back to you like the principle you know people come to our website we get the IP address we use clear bits to get the domain we score the company we find we prospect to find the right contact and we've send an email all right that's a very basic schematic about it right and we get just on that on our own website to see anonymous to reveal anonymous companies the intent of anonymous companies who don't sign up on our website get hundreds of them per day right and you think well great but you talk about automation how do you automate that because if we just drop it in Salesforce like such people are gonna die we're going to have more sales people that's exactly the opposite of what you want to do so we actually automate the entire outreach in the name of our salespeople we do not have as jaws adrift all right everything is automated to the point to demo and so whether it's anonymous visitors on a website or intent data we have discovered we will send very customized emails where we inject the knowledge of the company the person and the intent we have discovered all right look at this email look it's a good email but it's kind of missing a good illustration all right because best emails they have an image all they even have a gift all right and so the we look at what salespeople do and I have sped up this video of three acts if it works let's see they go so I've sped up that view of three acts of a sales rep actually building a preview of what my product drift looks on their website all right and so they basically go into a demo feature that we have for sales reps and they're gonna like layer a version of drift on top of the customers website right and they're gonna take a screenshot of that all right so they create a drift but whatever don't care about the product they go to the customers or the prospects website they use a little Chrome extension we build for that take a screenshot you can see here the stripped at the bottom that's customized with the right logo the right message they go into the Gmail they enter the our customers email they write a quick email and they're going to drop the image there right this is sped up this was rehearsed it usually takes them actually like six to ten minutes to do properly and I mean they don't do that like all day long and so like it's it's just exhausting for them right and there you go yeah very much but that mean back that clicks really well we look at that say hey how can we do that well if you analyze how it works and we talk about code eating the food chain well it's not it's not that complex it when we have API is to like take screenshots we could like tap into an API to build you know the preview and that's a good example for the goof team does right we've actually rebuilt a script to generate that exact screenshot at scale thousands of times per day and so this is slowed down 5x and that does exactly the same thing right so we have a couple of engineers then like they do that kind of stuff and so that's a good example of what the core team does by leveraging engineering to replace a high volume low frequency application all right and they go have a screen shot all right and then we merge that with the text we saw before now we have a text sent in the name of the sales rep of the AE customized the company the person the intent we have discovered we know that by we know they are in a buy motion with a preview what it looks on their website that's starting to be like 3d like customizing relevant relevant is or what's interesting when you look at actually what happens on slack or emails from customers customers say stuff like hey like like how did you end up sending this thing because you see here it says like hey have you thought you saw you interact and folding didn't post all that is 100% automated how you do that it's wonderful we have sales rep saying is that email from growth it means react wicked of reaching the cheering point where even our sales ops don't know if like a human sent it or if one of their buddies sent it right wrist is quite fun so if you go back to the schematic you say okay well you you pull the data you store it in like segments or whatever you prospect you score it and there's an email there's really two blocks here one is the collection of data and your own is action of data right and will the questions like why stop at email can actually do more than just one channel you can actually start leveraging that intent data and that's going models across multiple channels I'm gonna show you a couple examples obviously drifts so we leveraged that ourselves so the drift chat bot is personalized to the predictions were making although likely hurt you by and the intent was seeing so if we know that they're an intent motion we need to know that comparing us on judicata with a competitor we will push that into the chat bot I've built stuff that are pretty fun where we have a high prediction instead of telling people hey you like seems like you're interested in buying a Chad bar tool we'll push a chat that says hey how do you like your coffee on the home page right and so they can engage right and what's happening is I'm actually building an order that we actually send to send oh so who says that your posts mates and so we deliver hard drink within about 20 minutes in most metro areas that's one of those high prediction interesting this actually great cost because this is like about 15 to 20 bucks depending on like the how fancy the coffee is super cheap in b2b I don't forget my LTV is like above $10,000 if my prediction is high like 15 bucks investments to like create a memorable experience is like its peanuts because what happens so that guy in that company or that woman will just say hey I just want to drupes website in like I got a hot drink yeah right and so everyone goes there now the entire company knows about it right so we win other example we use in column eyes and disc I'm also an advice there it's kind of optimizing steroids we actually change the web page dynamically so within 0.2 to 0.5 seconds we use our predictions to change the content of homepage one example here we inject the name of the company in the in the header so here it was a visit from Salesforce and we will do some things like for example remove the pricing page entirely all the links to the pricing page will be removed will remove the trial but and we'll just say hey let's talk let's do let's do a demo why is that well if I have like it's a cratenbarrel or whatever like or Nike coming to our website I don't want them to see we have a $99 plan right that's that's not what my competitors on the enterprise market do all right I want to book a demo because they're experienced if they sign up it's gonna be miserable because the likelihood of Nike installing the drift chat on their own is 0 so it's plain Zeebo there's no chance right so it's not worth it and so we actually create multiple experiences and tracks depending on our predictions we also send those doges and handwritten letters at scale that's $5 for $5 we have our workers and us send a handwritten letter to our prospects Chen you think about it it's got like a shadow funnel right it's the follow before the funnel all right and you got like those those three stages and so if you map that into a grid you can say hey like this a walrus this consideration this decision right and you have multiple like scores of that very much like we have that kind of grid for leads right um how like the other two by and well they're on in the buying cycle is that we have that before they even come to us and so I talked a lot about costs and and margins right about optimizing the cost we're using the cost and so if you think about what we do now adrift we're actually collecting the data multiple times in the life cycle of that prospect and we're building a progressive score the score increases because we're we get more data points which means two things or confidence on our model increases and two we just see there's just more intense right what that means is that we can actually apply that to the LTV because if I know the likelihood of buying and I know my old TV you can just like multiply that and say hey like there's value at that time is like maybe a hundred bucks now I know how much I can invest depending where on the funnel that's interesting is that we've actually leveraged that a couple of weeks ago and this is a fun story because this is working really really well so um I've done a lot of spending on Facebook in SAS has been mostly frustrating because book is optimized for e-commerce and mobile games in terms of like how their a machine learning works to train learn who are the right people the ad should be a display - and the reason we does not work in SAS is because the conversion window that's allowed in facebook is seven days right and the conversion must happen a client-side and you must have s key use and different products I'm in SAS my conversions happen in Salesforce and they sure as hell don't happen in seven days alright so there's nothing I can do but just send like great audiences to them does not work what we do now is that we run the prediction client side real-time and we send back to Facebook of purchase events at the moment of the trial so when someone signs up make the prediction we send back the values of before in dollars to Facebook with a SKU as if it was a purchase and we Tuffy's but hey there's a purchase 200 bucks Facebook doesn't know any better okay fine purchase right and Facebook optimizes for more people like that we've been able to divide our cost per qualified lead by about 3x so we end from there about 160 bucks per qualified leads about 46 bucks all right and that's because we are training Facebook's ml with our own ml so the only thing I can train an ml system well is actually lots of good data and if you synthesize all of that it means we can have the right sorry the right action at the right time and we know the costs so we can apply the right spending at the right time before they come to us per account right and if we go back just simplifying we're just applying what b2c does there's no magic here like the word of b2c does that they did that like years ago we'll just bring that to to b2b and it looks like that right we pull all of those intents into a user record and we just then fan them out to all those channels I have three slides which I don't usually show just for you guys because this is a school and you guys are founders so a few confited contradiction slides what's all the results of last year and 2018 we had 11 so 116,000 buying signals that we're able to collect that generates a foot 8 thousand accounts of which like $40,000 I qualified ABC plus and we generated 1,300 demos it's quite a lot of there most of us either high conversion rate all that entirely automated and our staff looks like that so we pull like all the awards and discovery stack we process the data and we founded them out into the analytics there's a lot of tools there a lot of tools and so you might ask well what's the budget so it's about 270 cake of tech budget here at average 66 percent discount good discounts 3 back engineer so it's about a million dollar your budget so that's it Thanks

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