If you are in GTM ops (RevOps, MarOps, GrowthOps), you know where the goalpost is. You are here to make sure your prospects become high-value customers.
Your workflow may focus on stages, goals, funnels, or some other construct. You might be reaching out to contacts warm or cold. You are always looking for those users who want to convert to trials, see a demo, or have a sales meeting.
No matter how you are reaching out to your user, the end goal remains the same. Make them paid customers, upsell them for the highest possible revenue, and keep them for the long run.
To accomplish this, you probably have a lead generation process that has worked for you in the past. Maybe it looks like this:
- Build a list of marketing activities, like webinars, pop-ups, cold outreach, blogs, and content marketing.
- Validate this list to be sure they match your Ideal Customer Profile (ICP).
- Upload your list into a marketing automation system like HubSpot, Marketo, or Mailchimp.
- Create an email campaign. Or perhaps reach out to cold contacts, hoping to book a meeting or demo, entice them to a free software trial, or test a proof of concept (POC).
- Try to retain your prospect through a maze of strategies.
- Last but not least, build a huge rules engine with a lot of “if-else” loops, to determine if a buyer traverses your path.
Here’s the problem, though. This looks like a comprehensive process, but it is tedious to build and maintain. It also represents the under-utilization of first-party data, wasted hours, and growth opportunities squandered. Most of it is carried out with nothing but human intuition and traditional best practice. And most importantly, it relies on predetermined ideas of how your prospect will behave, rather than observing them to see how they actually behave.
Using this method, if you are a company looking for contextual communication with your customers you need an elaborate set-up to make that happen. Your context must be developed at the user level, with classifications for groups like ready-to-buy, trial users, upsell-ready, paid users, or win-back opportunities. It’s time-consuming, expensive, and difficult to accurately place a user in the right classification.
Do you want to trade heartburn for a headache?
You have traded the problem of how to reach your customers for a bigger problem. The tools to offer this level of segmentation require a huge effort. The rules configuration process needed for this process – conditionality, data, analytics – are manual and tedious. There’s no automated way to do this today.
In addition, your business is in possession of a vast amount of valuable first-party multi-channel data for your customer, and it is siloed away in disparate tools and operations. There are no easy integrations to put this to work for you.
Lopsided analysis and single-dimension contact qualification
Marketing in the digital age has undergone a revolution.
- In the beginning, growth was marketing to sales driven. Emphasis was on customer relationship management (CRM) and overall interactions. Growth teams focused on funneling marketing qualified leads (MQL) into sales qualified leads (SQL).
- In an effort to improve sales results, marketers turned to customer success metrics. Customer happiness and net promoter score (NPS) were used to gain a better understanding of the customer. But even with this new information, data silos were left unmined.
- The latest silver bullet for marketers is product usage data. This is no doubt useful information, and tools like Amplitude or Mixpanel make it easily accessible. But returns are still limited when you are dependent on only one signal. Don’t forget you’re also paying a ton of money to get this data.
- As data became richer and customer segmentation more available, there is still a barrier to peak results. GTM ops team are today limited to single channels of data.
You simply cannot identify the customers who are ready for their next steps – such as upsell, demo, or closing a sale – by a single channel alone. Single-channel analysis identifies many of the wrong contacts or leaves your best prospects out entirely.
Additionally, these channels completely ignore valuable first-party intent data like email campaign interaction, webinar engagement, customer support data, or billing trends.
Successful SaaS marketing needs more than a single-dimension focus.
Glance Rethinks Segmentation for SaaS Growth Context
We believe that any solution to an entrenched problem cannot be solved by incremental thinking alone. Our approach is to take a holistic view of the solution. This led to the creation of Glance.
The core of Glance is AI-driven, multi-channel, connected data with the power of Graph AI. We deliver:
Hands-free Smart Segmentation
It takes just a few minutes to connect your own channels of data to Glance, integrate it with your contact list, and tell us what your goals are. All of this occurs seamlessly through SSO and simple integration. Glance takes up all the heavy lifting from there with our proprietary Graph AI.
We determine the right mix of channels, and which events or metrics within them, make the most sense to deliver “hyper-segments” for immediate use at every point of the conversion, expansion, win-back paths. These hyper-segments flow seamlessly into your marketing email platform or CRM, or any other destination channel like customer success, sales enablement or customer engagement.
You don’t even have to define the events or metrics you want to use or create rules for segment creation. Glance takes the stress out of a formerly cumbersome process, and eliminates the uncertainty of “if-then” rules.
Multi-channel qualified contacts and leads
Identifying segments using a single channel of data, such as product engagement, produces lopsided results. And you have so much more data at your disposal – data like email campaign interaction, webinar engagement, customer support data, and billing trends.
Glance determines the best combination of channels for your particular goal and business type to create focused, relevant segmentation. We believe this is a much smarter way to look at the whole picture.
Connected multi-channel signals
Glance uses Graph AI – graph technology and artificial intelligence (AI) to connect a symphony of multi-channel signal data. This allows us to leverage machine learning, zoom into the right data, and deliver highly targeted customer segments that match your goals.
Right contact list right out of the box
By using intent data like CRM, webinars, and other enrichment sources, we can create ready-to-buy or ready-for-trial segments with a click of a button. GTM Ops teams and growth marketers know who the right target is as soon as they acquire contacts.
Here at Glance, we didn’t just join in the revenue growth revolution. We are turning it on its head. We deliver massive revenue acceleration by taking the fuller picture with our Graph AI.
Our AI-driven smart segmentation and content suggestions drive marketing outcomes in ways that just weren’t possible before. In our early customers, we have seen a 2.2x improvement in campaign success. Talk to us and we’d love to show you how we can bring this power to your GTM ops teams.
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