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WEBINAR OVERVIEW Learn how leading retailers are delivering a personalised customer experience in four steps with IBM

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WEBINAR OVERVIEW Learn how leading retailers are delivering a personalised customer experience in f
WEBINAR OVERVIEW Learn how leading retailers are delivering a personalised customer experience in f
In a recent Internet Retailing webinar, Learn how leading retailers are delivering a personalised customer experience in four steps with IBM, we heard from James Lovell, European retail solutions executive, IBM Commerce, in a session on conversion rate optimisation. Here's a bulletpoint overview of the webinar.

"I've worked with a number of leading brands around Europe and one of the topics that never seems to go away is personalisation and how to deliver a personalised customer experience," said James Lovell, European retail solutions executive at IBM Commerce as he opened the webinar.

The marketplace



• "We've seen the increase of the empowered individual" – consumers have more information, more power, and want more value and better engagement across the journey.

• Technology driving this trend. Starting to see challenges to the traditional retail model, with both the proliferation of digital devices and the digital experience in store.

• Black Friday: 2015 mobile sales reached 47% of all online sales, 15% up year-on-year. This year mobile sales set to become the dominant channel, with over 50%.

• Social media: "we're starting to see social media mature. Retailers and organisations are starting to figure out how they can leverage these insights." Moving from one-way to two-way dialogue with consumers.

• New technologies emerging: Amazon Dash - "putting product ordering at our fingertips, right where we need those products attached to the devices." Engagement methods through artificial intelligence and artificial reality. Rate of adoption may speed up and bring forward emergence of these technologies.

•  Perception gap: 81% of companies say they have, or are close to having, a holistic view of their customers – but only 37% of customers say their favourite retailer understands them. "There's quite a gap there that we all need to work together to close."

Using data to plug the gap



• Need to harness data and use it intelligently across the entire customer journey.

• Types of data: demographic/transaction commonly collected. But personalising the customer experience relies also on behavioural data and on interaction data. [Detailed diagram]

• Create a single identity to enable a personalised customer experience.

• Two types of personalisation: explicit personalisation – customer pull: preferred marketing channels, fulfilment method, payment method)

and

implicit personalisation: retailer-push personalisation through product/content recommendations, targeted and relevant marketing promotions, personalised email marketing, product landing pages specific to previous browsing behaviour, localised personalisation based on proximity to stores.

• Core competencies to delivering personalised customer experience

Analyse/decide, collect data, deliver engaging messages and capture reactions, manage marketing processes and measure results.

• Personalised customer experience depends on having relevant customer data and being able to exploit it.

Process



[with detailed diagrams]

1. Put the foundations in place: digital analytics, ecommerce, order management.

2. Rule-based personalisation: using customer insight platform, digital marketing and customer experience management. Capturing all digital customer interactions.

3. Real-time personalisation: adding in cross-channel marketing, and customer master data. Enables retailers to start visualising customer journeys across all channels.

4. Hyper-personalisation: extend to include social and competitor positioning.

Case studies: Homebase, Boots.

James then gave an overview of IBM Commerce and its experience.

The webinar was followed by a Q&A session, in which questions covered subjects from where retailers are missing a trick, through to the challenges involved in combining data from different programmes.

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