How to Select a CRM Solution for Your Company

This article will help you select a CRM solution based on several important criteria, such as features, technical functions and usability.

If you work for an SME company and still do not have a CRM (customer relationship management) solution in place, or would like to replace the current CRM solution with a new one, this article will be helpful to you.

Initial analysis

You will need to compare at least 5-10 solutions available on the market and evaluate both their technical and business feasibility and their features. The easiest way is to create a decision matrix in Excel, where you list the CRM solutions and the factors that are important. For a list of such factors, keep on reading.

Market presence

The first idea would be to go for a solution that is well-known on the market. However, it may not be the solution that fits the needs of your company or your line of business. For example, some CRM solutions with strong market presence are not geared towards the needs of small companies. At the same time, you do not want to end up with an underdeveloped product lacking documentation and support (see below).

GDPR

Choose the solutions that comply with data protection laws of your country or the countries you operate in. If technically feasible, select self-hosted instead of cloud-hosted solutions.

Integrations

Consider the landscape of the solutions you are already using. Your CRM system is the central component of this landscape. It should have integrations with all (or most) software you use or at least an open API to create such integrations.

Data import to a CRM solution

Most solutions offer data import from CSV/XLS files, as well as contact imports from Outlook (vCards). This will suffice in most cases. Some solutions offer data import through scanning business cards or from other sources (e.g. TXT files).

Data processing

Essentially, CRM is there to store and process data on your customers, leads, suppliers, partners and employees. Thus, the features of a CRM system must include an easy way to do all the following:

  • categorize contacts (e.g. tagging)
  • add comments and attach files to contacts
  • create relationships between data sets (e.g. associate people to companies)
  • change the entered data
  • (last but not least) back up and restore any data deleted by accident.

A good user rights management system will also be helpful (the more people are using the CRM the more helpful it gets :-))

Data export from a CRM solution

This is something that is equally important to data import. In case you want to migrate your data into another system or switch to another CRM, you should be able to do it without losing any important information.

Features

Do not get stuck on having as many features as possible. This will unnecessarily increase the complexity of the system and slow down the learning curve for everyone involved.  Instead, decide what features you actually need.  Here are some examples.

Sales

If your sales people will be using the CRM, consider how it tackles visualizing the sales funnel, lead management and analyzing the sales data.

Accounting

Some CRM systems offer automated creation of quotes and invoices as well as other payment tracking.

Support

CRM can become a solution that you will use for customer communication and support. If this is important, you might want to invest in CRM offering such features.

Project management

Many CRM systems offer project management features, such as setting up meetings, creating workflows, etc.

Usability

Usability is THE crucial factor in CRM implementation. The best way to test the usability of a product is to sign up for a trial version (make sure that no hidden costs or contract obligations arise after the testing phase).

Then you can start testing the software with an initial set of fake data, similar in structure to the data you will be using. If possible, let several relevant users from your company participate in this test.  In fact, you can even do some internal usability testing. Since this is rather time-consuming, select only 2-3 systems (that rank the highest in your decision matrix).

Support and Documentation

It would be best to test out the support or the documentation on the product during your testing phase. This way you will know how problems will be tackled in reality.

At this stage you should also check how your internal resources can support the implementation and introduction of the new software.

Cost

Do not let the price be the leading factor in selecting your CRM solution. If some free CRM software matches all of your requirements – go for it. However, if choosing a free solution involves hours spent on setting it up, bug-fixing and understanding how it actually works, you may want to give it a second thought.

Generally, the two pricing factors are the number of CRM users and the number of additional features (“Starter” vs “Premium” packages). Here I would recommend to start small and add any features when you will be sure that you need them.

The infographic below sums up the relevant factors in CRM software selection.

infographic how to select a crm solution

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A Comprehensive List of Email Analytics Metrics

In this article, I will describe 13 important email analytics metrics, what they mean, and how email campaign performance can be improved.

In this article, I will describe different metrics related to evaluating performance of email campaigns and how they can be improved.

Here is a typical funnel of an email campaign – from mailing list to conversion:

Subscription ⇒ Email Send ⇒ Email Delivery ⇒ Email Open ⇒ Email Click Through ⇒ Landing Page Visit ⇒ Conversion Funnel from Email ⇒ Conversion from Email

Let us review a set of email metrics connected with each step of this funnel.

  1. Subscription conversion = subscriptions / visits of the sign-up page. In order to get more people to subscribe, your sign-up form should have a clear call-to-action and ask only for necessary information. Short info on data protection will establish trust and offers of incentives (e.g. a free sample, a whitepaper download, etc.) will motivate more users to share their email address.
  2. Subscriber list growth rate = (new subscribers-old subscribers) / old subscribers. In order to constantly increase your subscriber base, you should both receive sufficient amounts of traffic to your subscription page and have a high subscription conversion rate.
  3. Number of emails sent. This is the starting quantifying point of email campaign funnel analysis. The only way to improve this metric is to increase the size of the mailing list. However, to ensure that the email addresses are valid and to comply with double opt-in procedure, avoid buying email lists.
  4. Delivery rate = number of emails delivered / number of emails sent. Delivery of the emails you send depends on several factors: white- or blacklisting of your IP by email service providers, existing or non-existing (hard bounce) email addresses, how full the recipient’s mailbox is (soft bounce), if a user has moved previous emails to spam, etc. In order to increase the delivery rate, make sure to revise your mailing list often and to remove obsolete or false addresses. In addition, you should always include a clearly visible Unsubscribe link and avoid using HTML-only emails with images.
  5. Open rate = number of emails opened / number of emails sent. This metric is greatly influenced by the subject and the timing/frequency of the emails sent. In order for the email to appear relevant for the user, you can apply segmentation and some degree of personalization to your email campaigns. When comprising the subject of the email, be precise and avoid words and expressions which can cause your email be filtered as spam.
  6. Unsubscribe rate = number of unsubscribe requests / emails sent. Clearly, it is best to keep unsubscribe rate as low as possible. In order to do this, make sure to deliver the message relevant to the recipient. In addition, high mailing frequency (e.g. once per day) will likely cause most users to unsubscribe (see my next post). Ideally, you should let the subscriber choose the mailing frequency optimal for them.
  7. Click-through rate = clicks on the links with the email / emails sent. In order to measure how many times a link in the email was clicked you can apply a campaign ID to the  URL, e.g. https://marketing-to-convert?cid=email&campaign=spring-break&link-id=001. In order to increase the click-through rate, the email CTA should be clearly visible and correspond to the email subject. You may also want to place links in the body of the email and  behind corresponding images. As has been stated above, the offer should be delivered at the right time and to the right user. Thus, factors such as user past activity and interests will play a role.
  8. Unique open and click-through rate. These metrics are basically the same as above however, only one open and click-through is counted per visitor (even if they interacted with the email multiple times).
  9. Landing page visits. Normally, this number will be equal to click-throughs. In case it is not, do review link tagging and check if there are any broken links.
  10. Cost per visit = total cost of a mailing campaign / number of visits to the landing page. Using this metric, you can compare the effectiveness of different campaigns. (The cost of a campaign is the cost you incur for sending an email multiplied by the number of emails sent.) Improving cost per visit can be achieved by generating more visits from your mailing i.e. by offering relevant content and compelling CTA’s.
  11. Landing page bounce rate = bounces / visits to the landing page. In order to decrease bounces on the landing page, make sure that landing page reflects the information in the link user clicks on. E.g. if you are making an email campaign about a particular product, do not send users to Products Overview page.
  12. Pages per visit from email. This metric demonstrates if users found your site engaging enough to move on from the landing page. However, a large number of pages viewed may signify that your site is difficult to navigate. Make it clear to the user where to go next from the landing page by integrating links or offering a small navigation menu.
  13. Conversion from email = number of conversions / emails sent. Bear in mind that conversion is not always a sale. Contact form submission, leaving a review or recommending your product to a friend can be counted as conversion actions. In any case, conversion rate will be the most important measure of your email campaign success. Optimizing conversion rate involves all stages of the funnel: from segmenting the mailing list to streamlining the user journey from the landing page.

This list is by no means an exhausting one but contains some important metrics that can be used to track the performance of email marketing campaigns.

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Divide and Rule: Types of Segmentation in Web Anaytics

In order to analyze traffic to your website you need to segment it. A lot of times, possibilities for segmentation will depend on the analytics system you use and the data you track. In this article, I will outline how you can create segments using the data commonly provided by analytics software. I will also evaluate, to what extent you can make use of the created segments.

First group of segments: user-based

Geo and tech characteristics of users belong to this group. If you have a way to find out the gender or the age of your users (registration, dialog windows), you can segment visitors even more granularly.

user-based-segments
User-based segments: by device type.

Geo-segmentation includes segmenting by cities, regions, countries as well as browser languages.

Geo-data is usually collected based on user IP. Although this information seems to be interesting (often presented in form of maps), it is only relevant if you offer a location-based product/service (e.g. only available in a few cities) or if your website is localized for several countries and you want to make sure that international users are routed to the correct country site.

Tech segments are based, for example, on device type or browser name and version, as well on as the user domain. From my experience, these parameters are not going to be used extremely often either. If you get a significant number of visitors from a certain device or a certain browser,  you should better make sure that your site works on them. Other than that, it useful to group sessions where an HTTP or a JavaScript error occurred (if an error is recurring and you can reproduce it, a fix is needed).  Additionally, IP address or user domain name are used to exclude internal traffic (i.e. the traffic from your company).

Second group of segments: content-based

As can be guessed from the name, such segments relate to the content of the site. In other words, by applying this segmentation, you can see what happens on certain parts of your website or on groups of pages. If set correctly, this gives a structured and precise insight into the website performance.

Some ways to apply this segmentation are:

  • By product (if you have a few products, e.g. 1-5)
  • By brand or by product type (if your website showcases a lot of products)
  • By department/division (if this is how your site is organized)
  • By content for different customer groups (gender, age, type of customer: business or private…)
  • By site component (forms, product description, FAQ…)
  • By country site (if the data is not split in the database)

This is by no means an exhaustive list. By looking at your site, you may come up with a more suitable (for you) way to segment content. Then you can use the grouping, for instance, to compare how different products perform or to create a product ranking by popularity/engagement.

Third group of segments: traffic-based

This type of segments will contain general break-up of traffic, without precise description of particular users. The most common segments will include: by traffic source, by referring domain, by time of visit (day of the week, hour).

New vs repeat/returning visitors segment is based on the cookie set on a visitor’s device (however, as a growing number of visitors do not accept cookies or delete them regularly, the data from this segmentation should be treated as an approximation).

Such segments are extremely useful in order to analyze how the performance changes depending on the type traffic flowing to the site. What is more,  traffic type will most probably have a larger impact on performance rather than user-based characteristics,

Fourth group of segments: interaction based

This is a large group of segment that describes how visitors interact with the site.

You can create segments by number of page views per visit (page depth), by bounce rate, by time on site, etc. For the majority of these parameters, you will need to come up data ranges, e.g. number of page views per visit may be split into the following segments: 1 view, 2-3 views, 4-6 views, 7 or more views. Besides, you can include events – such as forms submission,

This type of segmentation will enable you to start the analysis “from the other end”, e.g. what are the traffic sources or pages in best performing segments.

As you can see, applying correct segmentation to site traffic will provide you not only with more data but also with more insights into what influences the amount of traffic and its performance over time. But what if you feel that besides segmenting you need to group and generalize traffic somehow? This would be a clear case for cohort analysis, which I may talk about in one of the next posts.

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