Information for Marketing Managers

We recognise that the Marketing Manager is probably at the sharp end of delivery. It is their job to execute campaigns and analyse conversion rates. They don't have as much time as they would like to build insightful customer segmentation.

By automating the daily number crunching, marketing managers can invest time to explore customer interests and purchasing behaviours.

What all our clients have in common is their use of data to market more effectively. Their investment in translating data into information supports their marketing strategy and delivers actionable information to generate profitable marketing campaigns.

If any of the following resonate with you then please read on, if not, you may require some specific help or advice, please get in contact (details top right of this page).

Could customer propositions achieve higher conversion rates?

The best propositions will achieve greatest success when directed to the right customer at the right time - but who are they, what propositions and when should they be sent?

Analysis of conversion rates needs to take each element into consideration:

• Which customers were sent the proposition, how were they identified and why were they chosen?
• How did the proposition relate to the target audience, why would they wish to make a purchase, what was the rationale?
• Why were they sent the communication at that specific time, why then rather than some other point in time?

Behind all these decisions, will be supporting data analysis. As with all marketing activities, there is a need for testing, measuring the performance of each activity or marketing programme will provide a guide to future performance.

Analysis may emanate from the need to sell a product or service, or could be focused on customer purchasing habits, targeting specific propositions.

If the need is to sell a product, the first analysis task is to identify customers who already purchase the the product or a similar one. The analysis then needs to understand why those customers made their purchases:

• Did they buy it in combination with other products? If so, what were they?
• Was it a single purchase? What price did they pay? Was it on offer?
• Are they a frequent customer? What discounts were applied?
• What demographic sets them apart from other customers?
• Was there a common timing factor involved in their purchases?

These trains-of-thought analyses will aid identification of the best customers to target for the product proposition.

The alternative approach, is to start viewing propositions from a customer perspective:

• Which are the most valuable customers? What do these customers have in common; purchasing behaviours, demographics, interests?
• Are there similar customers based on demographics and interests, who have not made the same combination of purchases?

The benefit of this customer centric approach, is that propositions can be developed to meet know customer behaviours. Information Drivers provides a Business Opportunity Assessment service to help its clients discover these opportunities and build appropriate propositions.

Which are the best performing customer segments?

Customer segmentation is key to ensuring you market successfully to your customers.

Sometimes organisations think they need to buy in external lifestyle or business demographics in order to better understand their customers. Whilst there may be benefits from these data resources, the value of in-house data should not be overlooked.

We find that many organisations focus segmentation on locations. When dealing with businesses, they may use establishment type, Thompson's or standard industry coded (SIC).

In isolation, they don't provide much insight into what makes a customer different when compared to another.

When combined with a measure of customer performance they become far more revealing.

The classic method for measuring customer performance is to score each customer based on recency, frequency and value (RFV). This is sometimes called RFM, where 'M' is for monetary value.

• How recent was the last order placed by this customer - Recency
• How many times has a customer ordered on average within the last ‘n’ months - Frequency
• What is their average order margin for the period - Value

Interested in customer segmentation? You can find out more here.

Does the website convert visitors into customers?

There are many statistics that can be used to judge the success of a website; hits, page views, visitors, etc. but what really matters is did the website meet it's objective:

• On-line store, product purchases, cross-selling propositions
• Information portal for specific community, membership and or customer service
• Building brand awareness, advertising, etc

It is possible to assess:

• Brand awareness - how many unique visitors did you achieve after a campaign
• Click through rates and how much money is being generated
• How visitors arrive at your store, what they look at, what they come back too
• Which products and services are of greatest interest and which they buy
• Cross-sale opportunities, increasing average spend and profitability

IT departments typically have responsibility for ensuring websites are working, but it is marketing that needs to understand and manage website effectiveness. The marketing team may have access to various tools to help them e.g. Google Analytics, etc. but is the performance information in a form that management can judge the investments made in on-line marketing?

If like some of Information Drivers clients, you have an on-line business: an on-line store or membership based system, then it will be driven by an on-line database. Your website performance information when combined with data from the on-line database will provide a comprehensive view of what is happening in your on-line business.

Data quality issues affecting the ability to report information?

Some of our clients have had data quality issues, they now understand the need for good data and appreciate its value. It may be that system processes need changing, data capture rules implemented or perhaps data needs to be enhanced before to reporting. What ever the requirement may be, high quality data will help ensure that robust decisions are made.

It is essential for business to have a clear picture of its data and to understand  the reliability of its information. If data quality issues may be affecting the ability to generate accurate information, you could ask your IT team the following questions:

• How robust is the data? What business rules were applied at data entry?
• Focusing on the customer - do we know how and where data is stored in the system, which tables contain what information?
• Is information captured consistently and where not, what is missing?
• Are users forced to enter standardised information or are there fee text entries?

The results of data analysis are reliant upon the data which they are based. So whilst there is a strong need for data due diligence, lengthy data quality projects may result in significant delays and lost business opportunities.

Striking the correct balance between data quality and timely information delivery is essential. Most organisation have data quality issues, it is dealing with them in a pragmatic and effective manner that delivers timely and robust results.