Original subtitles

Hi everyone and welcome to the module on Lead Landscape assessment.

This forms an important step in your lead Gen planning process.

There are a lot of tables as this is essentially data analysis, but it will

give you some great insights.

In this module I'll be covering the

following topics. Analyzing your existing leads and sales

to determine winning buyer profiles.

Understand the best lead sources per

profile. Increasing conversion rates and setting

lead targets. So why is a lead landscape assessment

crucial? You have already done your market

research to understand the state of their market and opportunities and threats it

presents, as well as your competitor analysis.

This is the next stage, data analysis.

This process allows you to understand

current sales, what is and isn't working.

We then use these patterns and insights

to scale up.

It gives you a basis to compare.

Change to.

Only then can you really see what impact

your new lead Gen strategy will produce.

So let's get started.

This first section is about analyzing your existing leaves and sales.

Data is the key here, so let it do the talking.

Analyzing your existing leads and sales.

In this example, we're looking at lead

and sales data per week.

This gives us a snapshot of total leads,

total demos, total closed one sales.

Total closed deals value, average order

value, and various conversion rates.

How many leads and sales are you

generating on average? So over this seven week period it's 96

leads. And 2 5 new sales per week.

What are your main drivers to conversion? So the final action that converts them to

commit to the sale.

In this case, the example we're using is

booking a demo, but it could also be email, quote or trial membership for

example. Look at the conversion rate from

generating the lead to booking a demo.

And then again from booking a demo to

sale. On average the conversion rate from demo

to sale is 14 oh percent so % need one hundred demos to get fourteen sales.

On the average conversion rate from the point they've become elite to final sale,

it's 2 8-1 %.

Keep in mind what you can do to improve

these conversion rates, which we'll discuss later.

You can also see from the example the average order value per sale is 663$

Again, what could you be doing to improve this?

These numbers help you predict future sales if you can increase the number of

weekly leads to 200 for example, instead of the current 96 Using the average litre

cell conversion of 2 8-1 %.

You would assume you'll get 7 sails.

But this is quite a generic approach.

Overlaying more data will give you far

better insights. Let's look at buyer profile dimensions.

What else can the data tell you to make more informed decisions on where business

is coming from? Look at various dimensions within your

lead and sales data.

Are you getting more sales from

individuals with a high income, for example?

Or from a specific industry sector, geography or company size.

Work out if there are other parameters specific to your business.

Again, you'll be looking for patterns within the data.

Which demographics are important to your business strategy?

Who is your ideal client? For example, in this slide, the ideal

client is a recruitment agency with under 50 employees.

A job title of CEO, Managing Director, marketing director or head of marketing,

and they'll be located in North America.

If these demographics are crucial to form

your ideal client, ensure you have a way to collect this data.

Next, review your sales data by demographics.

Have a look at which have the highest average order value.

Which have the best lead to conversion lead times and conversion rates?

What are the quick wins worth investing in?

Focus on the segments that drive most value for your business.

We'll look at an example on the next slide.

Which demographics dominate and is this in line with your strategy and buyer

personas? What does it open up new profiles to

target and buy a personas to research.

Let's walk through an example.

Looking at industry in the sample data above in the first column.

Digital agency, hospitality and supplier are the top three profiles by a number of

sales. By average order value in the third

column. This changes to events.

Digital agency and theme park is the top three profiles and by nature, period.

In the last column, it changes again to education, hospitality and digital

agency. There are so many variables to consider.

For this reason, lead yield is a good holistic metric to use as it takes into

account both total leads generated and average order value.

It's calculated as total revenue.

Divided by Leeds generated.

It doesn't account for strategy alignment though or the other metrics such as

nature, period. So it really is a judgment call.

Events could be a one off with just one sale, but could also be worth exploring

as it has a high conversion rate and lead yield.

Ecommerce was a lower lead yield, has a high conversion rate and quick nurture

period. So again, could be worth testing.

For now, however, we'll presume your most profitable segments to target would be

digital agency, education, theme park and to explore events further.

This doesn't mean ignoring the other areas, it just gives you the insight to

inform your marketing strategy.

Generally speaking, focusing on the top

performing ones or one's most important to your business strategy is recommended

unless you have capacity for more and it's generating results.

What other dimensions can be explored? You could look at digital agencies broken

down further by company size.

Or size of the marketing team for

example. Or transportation companies based on

geographic region and the size of their fleet.

What other patterns can you find? Remember to base these on dimensions

useful to your business.

Collecting and analyzing data is

incredibly valuable, but don't collect data for the sake of it.

Create a process to collect the important data.

If number of email campaigns sent per week or how often they do grocery

shopping as valuable information to determine lead quality.

Make sure to add these questions to your lead forms.

However, avoid being too niche.

It's great knowing exactly who your

target customer is, but be mindful when it comes to targeting an ad, campaigns,

social media, or when building data that it could be limiting.

This section is to look at the source of the leads and sales you are currently

doing. Where are the bulk of your leads coming

from? What is the split organic versus paid?

And what can you do to increase more of the organics such as SEO improving

keywords or links in? Filter the lead source by the dimensions

and target profiles identified as important to your business.

Does this impact your target profiles? For example, if you do no paid activity.

But generate a lot of leads for a profile you hadn't focused on.

It would be worth investing to scale this up.

Likewise if you spend a lot on attracting a customer profile you thought was

important to your business.

But get little take up it's worth.

It's worth reviewing this.

What's working?

And he's amplifying what is, what isn't and should be reinvested.

Let's look at an example to analyse their source of sales.

This shows all sales made in a month by source.

Looking at the revenue generated in the second column.

You would think Facebook, email and Google Adwords were the best channels.

However, this doesn't account for the amount spent to generate the sales.

Customer acquisition cost and return on investment take into account both revenue

generated. And marketing costs, so give a bit a

better indication of channel performance.

However, they assume a single channel

attribution. So it's an indicator only.

On average, it's thought a customer has seven touch points before a sale.

They could have seen 3 emails from you.

An email from my partner.

To Google Adwords, Field searches, LinkedIn and then engage with your

Facebook ad. Single attribution only credits that last

touch point as the source.

So Facebook.

There is a multiple touch point model also.

However, for starting out, single channel attribution is far easier and gives you

enough of an indication.

The cat results tell us the best channels

to generate cells.

Our trade shows, partnerships, and email.

This only works assuming all factors are equal, such as how much effort was

applied per channel.

The quality of data.

Type of content etc.

So if your LinkedIn campaign was not

targeted, but Facebook was for example.

Facebook will more likely have the better

metrics. Continuing with the same example.

If we look at their potential for next month spend and revenue and spent the

same. 1750 on the same activity.

We're likely to get the same revenue sixty four thousand five hundred and

fifty six. However, focusing on the better

performing channels. So in this case, increasing spend on

Facebook by two.

And trade shows, email and partnerships

by three. You have spent the same on marketing.

But because these channels have higher return rates, your revenue would increase

to eighty eight thousand four hundred and eighty or more depending on how you

select and invest in your chosen channels.

That's a 37 % increase in revenue just by focusing on key performing channels.

Test the investment levels versus the channel selection.

Remember, multiple channels play into a sale.

On average, there are seven touch points before a sale.

So consider all benefits of a channel, including awareness, building trust and

driving traffic before cutting a channel completely.

It's safer to decrease the investment unless you know it's absolutely doesn't

work for you.

Analyzing the source of sales per

profile. You can dive deeper into channel analysis

by looking at which sources work best per customer profile.

This scenario shows it's best to target digital agencies on Facebook.

As it has the lowest cap at 83$ versus 100 on LinkedIn, which is highlighted in

red. But education companies on LinkedIn?

166 cat versus 500 on Facebook.

It also shows that targeted campaigns on

LinkedIn. Have a better ROI than general campaigns.

Reveal target profiles.

If your main target profiles have a high

CAC or low ROI, look to amend your campaigns or find other channels.

If lower priority profiles have low cax or high ROI's are they worth investing

more in as quick wins to scale up? This next section is to analyse and test

your conversion drivers and rates.

Improving conversion rates is another way

to scale up.

If your conversion rate on a live demo is

10 %, but you can increase this to 20 %.

You've essentially doubled your revenue

without any additional investment.

Track every touch point, phone calls,

form capture downloads, live chat demos and work out the conversion rates.

Which perform best? Which should you be doing more of, which

need further analysis to improve? Is the content right for the stage of the

buyer's journey? If they are problem aware.

But you are providing content at solution aware stage.

There is a mismatch.

Is the offer enticing enough?

If you leave, Magnet is a webinar, but you haven't tested alternatives like a

video or a white paper.

You don't know if these could be

performing any better.

If the data are of good quality, what are

your bounce and unsubscribe rates? Other campaigns targeted.

Is follow-up timely? At what point in the sales funnel are you

losing most prospects? Let the data guide you again.

Where are your weak points? What adjustments can you make and thereby

improve conversion rates? Outside of this conduct customer

research. What matters is what made the sales that

converted convert. Why did they choose our company?

What were the important deciders and features for the client?

And the Saint of the lost business.

What made them go elsewhere?

From the feedback you get, replicate the positives as much as possible.

And learn from the negatives.

In the same way, there are multiple touch

points responsible for the lead source.

There are multiple drivers to conversion,

but which are key? They've already got an interest in your

product or business.

How do you get them from there to the

sale? Is it a live video demo?

White paper offer? Phone call?

Which driver has the highest conversion rate?

And when you account for the resource required for this driver, is it still the

most effective? Again, keep testing.

For example, how do reps spend their time?

What makes most impact them closing their deals?

Are there repetitive processes during conversion that can be simplified or

automated to free up more resource? It's worth mentioning to look at patterns

in churn too.

How can you increase retention rates?

Existing happy customers are proven to spend more than new customers that are

yet to build up trust.

A 5 % increase in customer retention

produces more than a 25 % increase in profit, according to recent research.

Something to think about.

Conversion drive as best as resource.

In this example we're looking at the time required and conversion rate the various

drivers. In the table price quote email has one of

the lowest conversion rates at 6 %.

When you take into account the time

required for this driver, it becomes the most effective.

Ok. The others at the same time period.

Looking on the right, over the same 10

hour time period, emails could have driven 12 sales versus only 9 from demos.

Again, there are always other factors to take into account, but this gives you an

idea of which drivers to focus your resource on.

If customers spend more after one to one call, this may be your priority.

If a personal touch is important to your brand, then phone calls, demos and

consultations may need to feature more.

Or if it's about getting quick

information to people being efficient and ultimately most cells were the least

resource and email would be best for you.

Look at which types of customers convert

best and by which driver.

Or how the average order value changes

per driver? And adjust your strategy accordingly.

So perhaps the ecommerce profile has a higher average order value.

Through free consultation so you only offer this to them.

But cause an email have higher conversions for your other customer

profiles, so you save resource and use these in all other cases.

Again, work out the mix that works best for you, letting the data guide you miss.

The last area to touch on is setting lead targets.

This requires you to know your average order value, conversion rate, and your

target revenue. If all of your leads are classified.

As one score, you'll only need one column here.

However, in this example we'll assume you know the difference in performance

between your hot and cold leaves.

That isn't the case.

We'll touch on lead scoring later on in the course.

So back to the example here we're looking at a total revenue target per month over

seventy thousand dollars.

We're assuming 50 % comes from continuing

business and 50 % from new business.

Therefore, we've.

Created a 35,000 thousand revenue target per month.

For new business.

We know that hot leads.

Those that are very engaged convert at 20 % on average with an average order value

of 3000$ And that cold leaves.

Those that fit the profile but not very

engaged yet have a conversion rate of 1 5 % and average order value of 2000$ How

much do you normally get from each per month?

Use this to create your revenue expectation per these category.

So here.

I've assumed twenty four thousand five

hundred from hot and ten thousand five hundred from cold.

You may need to adjust this to begin with so it's in line with how these lead

categories typically perform, but it gives you a good starting point.

Next you divide twenty four thousand five hundred.

Your target for hot leads by the average order value of 3000 To find you need 8

customers. And to get 8 customers.

Divide 8 by 20 % conversion rate, so nought 2 which gives you the number of

leads required. Which is 40.

So 40 leads are needed at a conversion rate of 20 % to 8 customers and twenty

four thousand five hundred in revenue.

This calculation helps you gauge how many

leads are required overall.

Take a look at how many you achieve

already what and where is the short form.

And which are the best channels to drive

more activity to close this gap? And hit your target.

So in summary, we covered the following steps.

Establish the winning customer profiles to target.

What other data patterns exist in terms of clients with the highest value, most

relevance, or quickest turnaround time? Identify new profiles to increase

business. And create buyer personas for these as

well. Which are the best channels to reach your

target profiles? Keep testing and ensure you are

delivering low cax and high ROI.

Invest your budget in the winning

combinations of profiles and channels.

Improve conversion rates and drivers to

increase sales and revenue further.

Use conversion rates to identify the

number of leads required to hit revenue targets.

So that's about it.

Thank you so much.

I hope that's given you some insight into how to use your existing sales data to

drive an increase in sales.