All language subtitles for 1,2,Marketing landscape assessment

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.