Can a small or medium-sized business compete with much bigger ones?

Let’s skip all the usual over-intellectualizations and similar and jump right in. Yes. You absolutely can compete with bigger businesses and increase your revenues and profits. And it is easier than you think. The only thing you need to give up is the “yes but…” mentality.

Let’s just agree on some basics:

1. The only purpose of marketing is to sell stuff: products, services, ideas. Doesn’t matter.
2. The only purpose of advertising is to persuade a customer to buy that stuff. There are sub-categories of advertising: branding, direct… but ultimately, they exist to persuade someone to buy something.
3. There are only five steps to improving your revenues:

Understand the buyer ?? craft a persuasive message ?? deliver it accurately ?? analyze & learn ?? improve

Part 1 – Understanding the buyer

Understanding the buyer is the single most important task: if you don’t understand the buyer, nothing else matters. There are four layers to understanding your buyer. All of them are doable for a small or medium-sized business. Just approach them with an objective mindset.

1. Your transactions

Software you need: Excel, a CRM, and your own Point of Sale (POS) software (whatever you’re using)

Right now, you only have a person’s most basic information: their name, address, contact, what they purchased.At this point, while limited, there are already several things you could do to improve your revenues:

• Create a referral program so that your buyers refer you to other buyers. All you need is a decent CRM (like MailChimp’s Enterprise level) and the ability to divide the list using either tags or segments by perhaps the amount purchased, or the date, merchandise, or similar variables.
• Work on reselling your customers by sending follow up emails or direct mails with a repurchase order.
• Exporting the entire base to Excel will also allow you to analyze your base further by using Pivot Tables and other built-in tools.

Excel is part of Office (so most people have it), and MailChimp’s enterprise level software is around $60 or $70 per month.

Shooting ahead of the bird

• If you know your zip codes, you can use a tool such as Claritas “My Best Segments” to obtain very granular profiles of your customers based on their zip codes. This will give you a better understanding of your buyer.
• If you have their emails you can use Acxiom’s Personicx to also obtain a much more granular of the profiles of your buyers.

In each case, whether with Claritas, Personicx or both, you not only have to spend more money to get the information, you have to know what to do with it.

2. RFM – Recency, Frequency, and Monetary Value – a real database

Your next step should be to understand your customer base more thoroughly. Most people think that a CRM is a database and nothing could be further from the truth. A CRM uses a database called a CDP (Customer Data Platform) as its engine to create segments.

The three basic measures are:

1. Recency – when did the person purchase last?
2. Frequency – how often does the person purchase?
3. Monetary Value – How much did the person buy? (With the accompanying trending, meaning, a look at whether the person has been buying more or less over time.

A CDP doesn’t have to be expensive and/or complicated. ViewN, for example, can create a database from $89/month. A CDP takes your customer data and assembles it so that you have a more complete view of each buyer. With a CDP you move into a more complex but profitable territory.

A CDP will allow you to create detailed segmentation strategies and nurture campaigns using your CRM’s automated actions capabilities. Lost you yet? Hopefully not.

Here’s what a segmentation strategy might look like:

You can divide your customers into terciles, or groups of 1/3 of the base. The big advantage of using some sort of statistical division such as terciles or quintiles is that the base is easier to manage.

In this case, for example, we divide the initial variable (Recency) into 1/3rds: Bought recently, bought some time ago, hasn’t purchased in some time. And the way to do it is to just sort all buyers by their date of last purchase and take the upper 1/3, middle 1/3 and lower 1/3 and voila! We have terciles. Then you calculate the average for each tercile, and we have a working model.

We repeat the sequence for the “F” (Frequency) and “M” (Money) and wind up with 27 distinct groups that go from people who bought recently, buy frequently and buy big to those who haven’t bought in some time, bought only once and bought a tiny amount.

Then we create a strategy for each group (as the example shown above).

The only way this is possible is by using a real CDP to organize the information, then feeding that information to the CRM, which is the software pushing out the emails.

More complex? Absolutely. But… inexpensive, and eminently doable for most businesses.

Shooting ahead of the bird

• You will need to create a nurture campaign strategy – this is the content of the email, timing and their sequencing
• You will also need a copywriter to write the emails

3. Demographic information

The CDP gives you a solid “what”, “when” and “how much” for each segment. But you really don’t know the “who”. So, a doable next step is to add demographic information to each person in your base.

By demographic information we mean such variables as gender, age, marital status, educational attainment, presence of children under 18 at home and similar variables that make sense for your business.

So, imagine you were selling battery-warmed socks, you might want to collect some information about habits and usage. Like where do your customers use them (Bed? Outdoors?) and see if there are two completely different segments.

The easiest way to gather that information is through a survey which offers some sort of reward for taking it. The rewards could be a discount for everyone who answers, or a series of prizes randomly awarded to respondents, or similar other actions. Bottom line, you want many people to answer the survey.

Once you have the information, you do need a database to make sure the demographic information is paired with the right person and with the RFM information you already have.

Shooting ahead of the bird

The information collected at this stage will begin to inform the creative messaging of the second step.

4. Why? The holy grail of research

I have worked for some of the world largest ad agencies (DMB&B, Kenyon & Eckhardt, McCann-Erickson, Foote Cone & Belding) and some of the largest clients in the world. The huge difference (aside from, of course, huge sales) is that they spent money and a huge amount of time understanding why their buyers made the decisions they made: the why.

If you know why someone made a decision, it is easy to see that you can modify what they buy, how often, how much… it is endless.

The difference is that, today, understanding why people make decisions is more affordable and accessible than ever.

I will confess that the fixation with why is what drove me to co-found CEO Analytics.

There are many types of statistical analysis: factorial, regression, conjoint and more. Conjoint analysis is the most commonly used type when looking at how people make decisions. CEO Analytics uses something we pioneered: Disassociated Conjoint Analysis.

The central part of DCA is a custom slider that asks the respondent to choose between two random elements from a set of product or service attributes, one answer at a time.

Without going into excruciating details, the resulting information presents the scoring + relevance of every attribute, essentially, the why. Our methodology also eliminates all biases: content, order, ranking… so the information is as accurate and actionable as possible.

In following the utilitarian theme of this article, CEO Analytics is easily affordable by any medium-sized business and many small ones.

Shooting ahead of the bird

Conjoint analysis is used by major companies, such as telcoms, fast food restaurants and other companies that sell any sort of package or combination in order to understand the customer’s decision drivers. But it can be used for much more.

1. Test product or service attributes would be most desirable by customers. When joined with cost analysis, it can show a company which product or service features would be more profitable
2. Predict which marketing and/or promotional efforts will be more successful in each consumer target group

Bottom Line – The four stages of customer understanding

1. Basic information: contact, maybe some personal information
2. RFM: A CDP Customer data platform à What, when and how much
3. Demographic information à Who
4. Disassociated conjoint analysis à Why

Any medium-sized business and many small businesses can implement a complete program to understand all their customer segments cost-efficiently and quickly. That program would rival anything a large agency or company had 10 years ago. So, there is no excuse not to do it.

End of part 1