Prememoria: Reach is a sales enablement tool for hyper-personalizing outbound emails at scale in order to save time while obtaining higher response rates.
We’ve spent a fair amount of time thinking about the tools we need in order to make our sales operations efficient, effective, and scalable. There are plenty of tools to choose from but not all are appropriate for our early-stage as a startup. Over this and the coming two posts, we will go over the tools we’ve chosen and how we use them. This post will specifically go over our assumptions about our buyer personas and look at two of the tools we’re using; Apollo and Reach.
Buyer Personas
It goes without saying that until we have sufficient data we won’t know exactly who our buyer persona is. In our view however, it’s good to start with a few assumptions about who these people will be based on what we know about sales and sales teams. We have therefore decided to target the following roles for the following reasons:
- SDR Manager — SDRs (sales development representatives) are responsible for prospecting, reaching out and qualifying leads. Depending on the organization they may be qualifying inbound or outbound leads. In any event they spend a significant amount of time emailing and trying to set up meetings for the Account Executives. It’s our assumption that the SDR Manager wants to make their SDRs successful and more effective at booking meetings with the help of new tools/software.
- VP of Sales — The VP of Sales oversees all aspects related to the sales operations and, more importantly, sales targets and outcomes, of the organization. While not specifically focused on booking meetings, they are deeply committed to their team successfully hitting targets and making sure the Account Executives have active sales pipelines. It’s our belief that the VP of Sales would be interested in anything that helps fill the top-of-funnel.
- CEOs — We should preface this by saying that we are referring to CEOs of sub 100 person companies who will likely be very active in various departments including sales. We don’t think this applies to all CEOs. Given that many CEOs serve as the “routers” of the organization, passing opportunities and issues to the competent delegates, we believe that CEOs of relatively small companies would be interested in tools that could improve the efficiency of their sales reps and might therefore pass along our outreach email to the VP of Sales or SDR Manager to investigate further.
Tools (Part 1)
Apollo: Lead lists and email sequences
If you’re planning on reaching out at scale, you’re very likely going to need a well-researched database of leads. Some people build this in-house, others buy them pre-built and others use services where you can create them using filters. We opted for the latter so that we could continue to iterate based on the data we have.
We chose Apollo primarily for the quality lead lists one can generate using robust filtering. The cherry on top is that it also has an email sequencing tool built in and pricing is affordable relative to the value it provides (oh and contracts are monthly).
Reach: Hyper personalization at scale
We all know that personalized emails are significantly more likely to generate a response. It’s not trivial to meaningfully personalize your cold emails at scale given the time required in doing so (opening up multiple tabs, reading through linkedin profile, company website, news etc. and coming up with something interesting to say that shows the recipient that you actually spent the time to learn about them).
And that’s why we decided to build (and use!) Reach. Reach creates hyper personalized icebreaker messages for each lead based on LinkedIn, website and news sources. By using Reach we’re able to get higher response rates without spending a significant amount of time manually personalizing each email. It saves us countless hours and frees up our time as a team to focus on other aspects of our sales cycle and company.
Workflow
Step 1:
The first thing we need to do is create a custom variable in Apollo so that we can automatically fill that variable with the Reach icebreaker when we build our sequences. Just like you have variables like {{first name}} and {{company}} that get automatically filled for each lead, we need to create one for the {{reach message}}.
Step 2:
The next step is to start generating lists of leads that match our buyer personas and a few other requirements. We create separate lists for each persona. By using separate lists we can put them into unique sequences with unique copy that is relevant to that persona.
Then we introduce further filters such as geography, sector and company size. We are only targeting English speaking companies so we filter by North America and the United Kingdom.
We add a sector filter because we believe that companies working in B2B software a) are going to have outbound sales organizations and b) will be more sophisticated with the tech stack they use and therefore more open to new enablement tools.
In the case of VP of Sales and CEOs we add a filter to limit the company size to under 100 employees. It’s our belief that mid-sized companies will have faster sales cycles and can more quickly test and make decisions around tooling. For SDR Managers we don’t limit size since SDR Managers tend to work at larger organizations.
All that’s left to do is export the lists in batches in the form of a CSV document.
Step 3:
With our lead list in hand we can make use of Reach. We can import the CSV that we exported from Apollo straight into Reach. Apollo gives us lists that contain the lead’s LinkedIn profile URL as well as their company URL. Reach gives us the option to select which column we want to use for generating the personalized icebreakers.
Reach generates two icebreakers for each URL. We need to go through the results page and read through the messages one by one. We can select the option we like best and or make modifications to it directly in the text box if we see easy ways to improve it. If we’re unsatisfied we can hit regenerate to get another two options to consider.
With our icebreakers selected, we can export the results as a CSV from Reach. The output CSV will be the exact same lead list we imported into Reach with a new column called ‘Reach Message’. With this CSV we have everything we need to import back into Apollo (or MixMax) for our email sequences. The custom {{Reach Message}} variable we made in the beginning will be filled as easily as the {{first name}} and {{company}} variables from our lead list.
In our next post we will talk about how we use Reach with MixMax and why we decided to add a second sequencing tool to our stack.
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