|03-07-2018 11:19 AM CET - IT, New Media & Software||
Don’t Sell - Help People Buy: With Mark Godley, President at LeadGenius
Press release from: MarTechAdvisor
Mark Godley, President at LeadGenius shares key insights about choosing the ideal vendor data partner. According to him, an ideal client is someone who has the ambition to win with data but also someone who has tried and perhaps failed with data in the past and knows the practical challenges of working with data. Mark is a C-Suite Start-Up Junkie. Also, a proud and committed father, spouse, citizen, reader and aging athlete.
Watch Mark Godley’s interview at www.martechadvisor.com/interviews/sales-enablement/dont-s... .
Check out these memorable moments from Mark’s interview:
0:08- Is there a fundamental difference between how CMOs could be using data for lead generation for inbound vs. outbound marketing?
2:41- How should the ‘B2C-fication’ of B2B buyer journey impact a CMO’s approach to lead generation?
4:40- Once the data-basics are in place, how does a CMO find the ideal ‘data vendor- partner’?
6:43- What are the recurring mistakes you see CMOs and CSOs make with their basic martech stack and sales tech stack?
8:36- Where does LeadGenius fit in the present-day ‘data-solution alphabet soup’ of CDPs, DMPs, CRMs, ABM etc.?
10:08- What does an ideal client look like for LeadGenius?
12:15- What upcoming lead gen and data trends are you excited about?
Is there a fundamental difference between how CMOs could be using data for lead generation for inbound vs. outbound marketing?
Yeah, I do think the most sophisticated data users see a data strategy for both. But I'll give you a couple examples.
In both cases, I think it has to do with qualification - and the current term for qualification is Account Based Marketing, ABM.
We didn't call it that back in the day - who knows what it will be called five years from now. But for now, there's this concept of: ‘let me define who my ideal customer is - both at a company level and a person level - then let me apply scoring to figure out how good or bad a particular prospect is.
So how does that apply to inbound? That applies to inbound because someone may download a piece of shareware, someone may fill out a contact form, someone may grab some content off your website - by doing so you're collecting information on that person. Well, what you may find is that person comes from a company that scored very highly but the person him or herself needs to be added to, to figure out the whole buying center. So, companies are often partnering with third-party data vendors to append inbound form fill with additional information for better scoring and lead ranking.
Then from an outbound standpoint the predictive folks and the analytics folks are helping us understand that developing look-alike models or scoring companies to go find more like your best customer is a very effective way to target an expensive resource which are your highly paid marketers and sales reps to help them focus their efforts on the subsets of the market which is most likely to yield the best results.
• For Inbound marketer, it’s important to work with third-party vendors to enrich company and person details captured with advanced data points
• For outbound marketers, developing look-alike models and scoring models are crucial to reach the best prospects.
How should the ‘B2C-fication’ of B2B buyer journey impact a CMO’s approach to lead generation?
The main thing that's happened is the information scale has tipped. Going back to when I started in the late 80s, the sales rep was the main channel of information for a potential buyer. Now we have this thing called the interweb - the internet has developed and all of a sudden, a buyer can do all kinds of research and learn so much but the role of the sales rep and the role of the marketer has changed.
So back to the term I use - and I tell this to my sales and marketing team -
Our job is not to sell anyone. Our job is to help them buy and by helping them buy, it's about education.
It's about being crisp in our messaging, about how are we different. What do we do versus what we don't do. So being very clear and comprehensive in helping educate that buyer - I think is really important for marketers. The more you can be respectful and educate the buyer, I think the more likely you can set up the qualification process.
So that the only people that enter it are folks that have frankly self-selected a little bit and maybe a lot of opting out. If that means you've got this tight funnel with higher close ratios, I think you're doing ultimately your sales team a service by allowing people to filter themselves out early, by providing comprehensive and crisp information as to what you do and don't do.
• Don’t’ sell - help people buy
• Enable prospects to ‘self-select themselves’ into the funnel by being clear about what they will get from you.
Once the data-basics are in place, how does a CMO find the ideal ‘data vendor- partner’?
Once you end up going down a multi-vendor strategy - and I really see the majority of companies that I've interacted with the last ten years have either already gone there or they're considering it - you have that baseline relationship and you're going to add on top of that. Technographic, intent, or something else.
Once you get to a multi-vendor strategy, the concept of data co-ordination becomes very important.
Because you need to make decisions. Where are you going to connect this information? Are you going to put it in your marketing automation system, are you going to put it in your CRM, are you going to map it back and forth? How are you going to stitch it together or use a key such as an email address? And then, who are you going to present it to? Are you going to present it to your BDR team or to your marketing automation team or your CSM team?
So, the whole concept of data intake, data coordination, data distribution, in defining markets, in marketing outreach, in BDR interaction, in opportunity augmentation, in upsell cross-sell - thinking about how you stitch all of that, all those factors together is not a trivial undertaking. And that's why having staff with some technical chops can be really important to understand how do you start down this road.
An ideal data partner helps:
• ‘Co-ordinate’ the data points and help connect the dots
• Make decisions and accurately present the right data to the right audience
• Bring the technical muscle required to make that possible
What are the recurring mistakes you see CMOs and CSOs make with their basic martech stack and sales tech stack?
So, a common mistake is people thinking that if I just get one more credential, my life is going to get better. There's not enough focus on process, in people. They really are two legs of the stool on top of the tech stack. So, I think
Focusing on process and people and stopping the chase of ‘the next (tech) credential is going to set me free’. The shiny object syndrome is a mistake I often see people make.
Also, going back to that sales and marketing alignment - not getting agreement as to what are we trying to accomplish. Here at LeadGenius, we actually don't have any marketing goals. We have a bookings goal that marketing contributes to and then we have a client retention goal that marketing contributes to. So, again we're kind of practicing what I'm preaching It doesn't matter unless it results in a client that renews, in a client that you sign in the first place’.
The most common sales tech and martech mistakes:
• Ignoring Processes and People in favor of adding more tech components to the stack
• Not aligning sales and marketing goals behind business goals
Where does LeadGenius fit in the present-day ‘data-solution alphabet soup’ of CDPs, DMPs, CRMs, ABM etc.?
I talked earlier about the growing complexity of multiple data sources and trying to convert that into actionable information.
LeadGenius is right in the middle of that conversion. We are a data service that clients bring on board to make sense of converting all of that information, appending it, de-duping it, filling in whitespace, adding custom information that you can't buy off-the-shelf.
The ultimate goal of which is either to define a market better or from an ABM strategy, focus on the right customers and put information in your sales reps or marketing hands.
So unlike folks that sell data, with us, the end-result of what we sell is data but what you're really getting is a data service. You're getting people who augment internal staff to do the data cleanup, data management -all that is very difficult to do in-house. And we have tools to do that, that are very specialized in the work we do.
What does an ideal client look like for LeadGenius?
Someone that has tried on their own to do some of this data wrangling, brought in multiple vendors. Maybe they even tried an outsourced partner of some form or fashion. It's difficult for people to understand what we do and the value we bring, if this is your first time trying to create that data link or aggregate unstructured data and turn into structured data
Some people think that I'm just self-serving and talking about this minefield of challenges. So, we prefer to interact with folks that have tried to go it alone that have seen that this is not as easy as bolting on some APIs, duplicating some fields within systems and all of a sudden, you've got this world-class system.
We like experienced folks. We also like folks that have tried it on their own because that shows us they have the ambition, the willingness to risk, the willingness to fail and pick themselves up and dust themselves off.
Back to some of the other themes that we talked about - marketing and sales alignment is very helpful for us because sometimes we get brought in and instead of them pointing fingers at each other they start pointing at us. Then we end up trying to arbitrate between marketing and sales expectations – if there is no overlap, we're going to fail! So, we try to avoid those situations but sometimes we end up being the outside party that can actually get them to the table to find the common ground.
Ideal data-driven organizations:
• Have tried to self-manage data in the past
• Understand the complexity and challenges of data
• Have aligned sales and marketing teams
What upcoming lead gen and data trends are you excited about?
I think this concept of data access and data ubiquity. Individuals -their ambition outweighs their ability to execute. I think that same gap exists for us as an industry.
What I really look forward to happening is - I don't think we're going to reduce our ambition but I think our ability to meet the ambition, it is going to grow.
To some degree, I think all of us - marketers and go-to vendors - we're going to cross that chasm together. Instead of having outliers, cracking this code of how to use data, how to build a sales and marketing stack that really drives personalization at scale and a process that allows people to buy respectfully rather than try to grind a buyer into submission. Unfortunately, that is what I see a lot of these days.
I think we're going to have a much more enlightened process over the next couple years. I think we're going to see -we talked about APIs and connectivity - I think the average application is going to be interoperable - which is going to make some of this middleware stuff less important. And I think those things are going to allow us to optimize the buying process so that we're helping people buy more effectively which I hope leads to more client longevity and more satisfaction along the way.
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