dmi

Section 508

May 23rd, 2014

Get your mobile analytics right

Earlier this year, a major restaurant chain asked us if we could come up with a mobile concept that would enable them to learn more about their customers. They told us that they would dedicate a significant budget purely based on getting customer insights and analytics.

Clearly this plan was the wrong way round as you always need to start with a customer proposition before you can gather any interesting insights.

Despite this, most of our customers are still either:

a) not prioritising data collection and analytics as part of the scope of projects
b) not using the data they get out of the mobile solutions they already have

Data collection is the most common use case for beacon technologies as well as the key differentiator for many mobile start-ups that are disrupting existing industries. Companies such as Uber, Lyft, Airbnb and Evernote have taken analytics and insights to their hearts, measure and test everything and use it to constantly improve their services. We can only imagine how Facebook, Google and Twitter use all of the data they gather about their users.

Remember that data is there to help us make good decisions.  In order to make good decisions we need to know what what questions to ask, make the relevant hypotheses, and have the data tell us if they are true or false. The first step in this process is to define what we want answers to, and try to understand the data from different angles.

When the data received is not what we were expecting, it is then that we need to inspect closer and ask the next set of relevant questions. For example, we may find that many people download an app, but use it for 10 seconds on average- is this what we were expecting? If not, then start analysing the data and ask more questions which may help shed more light. Some examples of the information organisations track include, amongst others:

  • Store and other venue visits – frequency, time inside, where in the store, where do they spend most of their time
  • Conversation rates through the app or website – drop off rates and feedback during the customer journey
  • Conversation rates for transactions – specifically looking at differences and disruptions in transaction rates
  • Location information and behaviour – where was the user before they arrived and where do they go next?
  • Behaviour information about the customers – what are they interested in, when and how do they engage?
  • Social engagement patterns – is the customer an influencer, how many friends do they have, what content do they share?

When implemented correctly, data collected from mobile services as well as the analytics and business intelligence that follow, can be extremely valuable and turn into a differentiator for your organisation.

Think about what your mobile analytics and customer insights strategy should be, discuss and ask questions.

Read our previous blogs about setting KPIs and making an impact.

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Tags: analytics enterprise mobility

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